Parameter optimization method of electromagnetic shielding device based on differential evolution and ray tracing algorithm

Abstract

The present invention discloses a method for optimizing electromagnetic shielding device parameters based on differential evolution and ray tracing algorithms. The method comprises the following steps: modeling the scene to be simulated using a three-dimensional projection plus height method, presetting electromagnetic interference points and protection points, and related information; mapping the electromagnetic shielding device to individuals in the population of the differential evolution algorithm, initializing individual parameters, and setting key factors for differential evolution; simulating the simulation points using a full three-dimensional reverse ray tracing algorithm, and retaining or adjusting individual parameters based on the results; selecting the best individual from the retained individuals, and using its parameters to adjust the power, frequency, and position of the electromagnetic shielding device. This method effectively solves the problem of difficulty in distinguishing interference points from protection points and multiple frequency points in electromagnetic interference, avoids accidental interference damage, and can more efficiently optimize the parameters of the electromagnetic shielding device based on actual scenarios.

Description

Technical Field

[0001] This invention belongs to the field of communications technology and, more specifically, to a method for optimizing electromagnetic shielding device parameters based on differential evolution and ray tracing algorithms, which is part of the field of radio wave propagation prediction modeling and optimization. This method can be used to provide an interference decision-making tool for specific frequencies and regions in complex environments, thereby adjusting various parameters of an electromagnetic shielding device. Background Art

[0002] Electromagnetic jammers are being used in a growing number of security scenarios. Electromagnetic security control involves pre-programmed interference targeting specific frequencies and areas. A common example is signal jammers in examination rooms, which sweep across the entire frequency band to emit interference signals across the entire frequency range. This distorts valid signals emitted by electronic devices like mobile phones, preventing them from being interpreted by base stations, thus achieving signal blocking. However, in practice, this traditional approach is prone to false interference due to its inability to distinguish valid signals from those intended for jamming. Furthermore, due to the complex nature of actual application scenarios, simply increasing the power of the signal jammer to forcibly distort malicious signals not only compromises radio wave propagation but is also costly and ineffective in effectively targeting specific interference areas. Therefore, it is crucial to develop an optimal jamming strategy for specific frequencies and areas within complex environments, thereby adjusting the various parameters of the electromagnetic jammer to achieve targeted signal blocking.

[0003] Xidian University disclosed a method for adjusting jammer parameters by using multi-target jamming decision-making in its patent application, "A Multi-target Jamming Decision-making Method Based on MOPSO" (patent number CN 202311686838.6, application publication number CN 117706494 A). The implementation steps of this method are: (1) setting up a "many-to-many" confrontation scenario between unguided radar and jammer; (2) establishing the objective function of the jamming decision-making model, and calculating the jamming effect through the objective function. It is necessary to define the correlation matrix and derive the target parameters of the jamming decision-making model; (3) implementing the MOPSO optimization algorithm to optimize the jamming decision-making objective function. The optimization result is the jammer station layout result; (4) selecting different tendency solutions for the multiple results of step 3, and selecting a tendency Pareto solution according to the task requirements. Although this method can achieve a unified allocation of jamming resources, it can achieve the maximum jamming benefit. However, this method still has the following two shortcomings: First, in actual situations, it may be necessary to suppress interference on multiple frequencies at the same time. This method is applied to the "many-to-many" scenario, but does not consider the situation where the jammer can cope with multiple frequencies, resulting in the inability to suppress interference on multiple frequencies; second, this method does not consider the whitelist. During the interference process, there will still be some devices or areas that do not need to be interfered with. In actual application scenarios, it is necessary to distinguish these different devices or areas.

[0004] Xidian University disclosed a method for dynamically adjusting interference equipment parameters based on linear programming in its patent application "A dynamic collaborative electromagnetic suppression method, system equipment and medium based on linear programming" (patent number CN 202311851617.X, application publication number CN 117793911 A). The implementation steps of the method are: (1) Suppression task analysis and parameter initialization in the electromagnetic suppression area: clarify the specific frequency bands and specific targets that need to be suppressed in the electromagnetic suppression area and the whitelist devices to avoid accidental injury, and initialize the suppression requirements of the suppression signal strength and effective suppression time ratio of the suppression frequency; (2) Modeling of the collaborative suppression power optimization problem: for the suppression task of the electromagnetic suppression area in step 1, the problem is modeled with the suppression signal strength and effective suppression time; (3) Constructing the minimum effective interference device set of the suppression frequency: measuring the suppression effect of the collaborative suppression of various suppression devices by calculating the received signal strength at the typical suppression point or specific target; (4) Calculating the optimal suppression time ratio: constructing a linear programming problem on time ratio optimization, and using the M simplex method to solve the constructed linear programming problem; (5) Calculating the optimal collaborative suppression frequency: constructing a linear programming problem on collaborative power optimization, and using the large M simplex method to solve the linear programming problem to obtain the optimal collaborative suppression power; (6) Evaluating the suppression effect of the electromagnetic suppression area, checking the blocking situation of the communication equipment on each suppression frequency, and increasing the effective suppression time ratio of the frequency that does not meet the suppression requirements. This method can achieve electromagnetic suppression at multiple frequencies, with high efficiency and minimal collateral damage. However, it still has the following shortcomings: While this method proposes multi-frequency electromagnetic suppression, which can address the frequency band issue, it does not consider the relocation of interfering devices and ignores the portability of devices. This results in the calculated minimum power not necessarily being the actual optimal value. Summary of the Invention

[0005] The purpose of the present invention is to address the shortcomings of the above-mentioned existing technologies and propose an electromagnetic shielding device parameter optimization method based on the combination of differential evolution and ray tracing algorithm, aiming to solve the problem of precise and efficient electromagnetic suppression and protection in complex environments by adjusting the electromagnetic shielding device parameters.

[0006] The technical idea for achieving the purpose of the present invention is that, since the present invention utilizes the idea of ​​combining differential evolution and ray tracing, appropriate mutation operators and crossover operators are selected, the parameters required for ray tracing are treated as an individual, and the interference points and protection points are abstractly extracted as simulation points to perform electromagnetic simulation. By comparing the interference threshold with the protection threshold, the parameters of each individual, such as frequency, power, and position information, are continuously optimized. This solves the problem that the existing technology cannot suppress interference at multiple frequency points at the same time. For traditional genetic algorithms and simulated annealing algorithms for multi-target interference decision-making, premature maturation and falling into local optimal solutions will occur during each population iteration process, and the commonly used forward ray tracing algorithm will track a large number of rays, wasting a lot of time, and it is impossible to select the right individual in a short time. The present invention provides a method for obtaining the optimal solution parameters of the electromagnetic shielding device by simulating and predicting the power coverage of the electromagnetic shielding device based on differential evolution and full three-dimensional reverse ray tracing algorithm in classic urban scenarios, taking the electromagnetic shielding device as the signal source, the interfered point and the protection point as the simulation points, and the method can not only effectively solve the above-mentioned difficulties and the problem of slow simulation efficiency, but also make the simulation effect more realistic and reliable, and avoid the problem of errors caused by the internal limitations of the algorithm in specific urban environments.

[0007] The specific steps for achieving the purpose of the present invention include the following:

[0008] Step 1: Use 3D projection plus height to model the simulation scene, determine the locations of electromagnetic interference points and electromagnetic protection points, as well as the interference threshold range and protection threshold range;

[0009] Step 2: Each electromagnetic shielding device corresponds to an individual in the differential evolution population, initializes the position, power, and frequency parameters of each individual, and sets the key factors in the differential evolution algorithm;

[0010] Step 3: Treat each electromagnetic interference point and each electromagnetic protection point as a simulation point, treat each electromagnetic shielding device as a signal source, perform full three-dimensional reverse ray tracing simulation on each individual, and predict the power coverage value of each electromagnetic shielding device at each electromagnetic interference point and each electromagnetic protection point;

[0011] Step 4: Determine whether each power coverage value is within the interference threshold range or the protection threshold range. If so, retain the individual parameters and execute step 5. Otherwise, use the individual's current parameters as a reference point, make small adjustments to them by a certain fluctuation value, and then execute step 3.

[0012] Step 5: Calculate the fitness function value of each retained individual, and select the function value closest to 0 from all fitness function values ​​as the best individual to set the position, power, and frequency parameters of the electromagnetic shielding.

[0013] Furthermore, the method of using three-dimensional projection plus height to model the scene to be simulated means starting from any vertex of the polygon corresponding to the top view of the obstacle to be modeled in the scene to be simulated, recording all vertices in a clockwise direction, and connecting two adjacent vertices to represent the top view. Figure 1 Edges are added and a height is assigned to each polygon in the top view, eventually forming a cylinder to complete the modeling of the entire scene.

[0014] Furthermore, the electromagnetic interference point position refers to the position of multiple interference signal points emitted by a preset electromagnetic shielding device in the scene to be simulated according to user needs, and each interference signal point cannot overlap with an electromagnetic protection point.

[0015] Furthermore, the electromagnetic protection point position refers to a plurality of protection points preset in the simulation scene according to user needs that are not interfered by the interference signal emitted by the electromagnetic shielding device, and each protection point cannot overlap with the electromagnetic interference point.

[0016] Furthermore, the interference threshold interval refers to an independent power interval preset for each electromagnetic interference point. The power interval range can be reasonably set by the user according to actual needs, and should not be too large or too small. When the interference signal power value received by the electromagnetic interference point is within this interval, the point is considered to have been interfered with.

[0017] Furthermore, the protection threshold interval refers to an independent power interval preset for each electromagnetic protection point. The power interval range can be reasonably set by the user according to actual needs, and should not be too large or too small. When the power value of the interference signal received by the electromagnetic protection point is within this interval, it is considered that the point is not interfered with.

[0018] Furthermore, the full three-dimensional reverse ray tracing simulation of each individual means processing the preset electromagnetic interference points and electromagnetic protection points as simulation points of full three-dimensional reverse ray tracing; then treating each electromagnetic shielding device as a signal source, and using full three-dimensional reverse ray tracing to simulate the simulation points in the scene to be simulated.

[0019] Furthermore, the predicted power coverage value of each electromagnetic shielding device at each electromagnetic interference point and each electromagnetic protection point refers to the power of the interference signal emitted by the electromagnetic shielding device minus the path loss corresponding to each simulation point, so as to obtain the power coverage value of each electromagnetic interference point and each electromagnetic protection point; its expression is as follows:

[0020] P i =P t -L i

[0021] Among them, P i Indicates the power coverage value received by the ith simulation point, Pt Indicates the transmission power of the electromagnetic shielding device, L i represents the path loss of the i-th simulation point.

[0022] Furthermore, the small-range adjustment of the certain fluctuation value refers to adding a different random value to the X, Y, Z coordinates and power value of the current position of the electromagnetic shielding device respectively, and the value of each random value cannot exceed the boundary value of the modified parameter. If the modified parameter value exceeds its corresponding boundary value, a new random value is selected and the parameter is modified again until the parameter value of the parameter is modified within its corresponding boundary.

[0023] Furthermore, the fitness function value of each retained individual is calculated by the following formula:

[0024]

[0025] Among them, F h represents the fitness value of the hth retained individual, k b represents the interference weight factor, p bsi represents the power coverage value obtained by full three-dimensional reverse ray tracing algorithm simulation at the i-th electromagnetic interference point, p bi represents the interference threshold power of the i-th electromagnetic interference point, i = 1, 2, ... n, n represents the total number of electromagnetic interference points, k w represents the protection weight factor, p wsj represents the power coverage value obtained by simulating the full three-dimensional reverse ray tracing algorithm at the jth electromagnetic protection point, p wi k represents the protection threshold power of the jth electromagnetic protection point, j = 1, 2, ... m, m represents the total number of electromagnetic protection points. b and k w The value of is selected in the range of (0, 20] to ensure that the result of each item is greater than or equal to 0.

[0026] Compared with the prior art, the present invention has the following advantages:

[0027] First, the present invention uses a full three-dimensional reverse ray tracing algorithm in a specific urban environment, takes the electromagnetic shielding device as the signal source, and the interfered point and protection point as the simulation point, and simulates and predicts the power coverage of the electromagnetic shielding device, overcoming the problem of slow simulation efficiency in the existing technology, so that the present invention can accurately achieve multi-frequency and multi-point suppression effects, the algorithm has better robustness, and can more accurately adjust the parameters of the electromagnetic shielding device.

[0028] Second, the present invention combines the full three-dimensional ray tracing algorithm and the differential evolution algorithm, which not only avoids premature phenomenon, improves the algorithm convergence, and increases simulation accuracy, but also the differential evolution algorithm continuously modifies the power, frequency, position and other parameters of the electromagnetic shielding device, so that the present invention can adjust the parameters of the electromagnetic shielding device in more complex scenarios. While suppressing the interference electromagnetic in a fixed, precise and efficient manner, it can provide effective protection for the electromagnetic signals of the protection point. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a flow chart of an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a simulation environment according to an embodiment of the present invention;

[0031] Figure 3 A schematic diagram of a simulation environment modeling according to an embodiment of the present invention;

[0032] Figure 4 Schematic diagram of the distribution of electromagnetic interference points and electromagnetic protection points according to an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of the average fitness value of individuals in the population during 22 algorithm iterations of the simulation experiment of the present invention;

[0034] Figure 6 This is a schematic diagram of the optimal fitness value of individuals in the population during the 22 algorithm iterations of the simulation experiment of the present invention;

[0035] Figure 7 This is a schematic diagram of the position results of a group of electromagnetic shielding devices after the simulation experiment of the present invention is iterated based on differential evolution and ray tracing algorithm. DETAILED DESCRIPTION

[0036] The specific implementation steps of the present invention are further described below in conjunction with the drawings and embodiments.

[0037] Reference Figure 1 , further describing the specific implementation steps of the embodiment of the present invention.

[0038] Step 1: Model the simulation scenario of the embodiment of the present invention using a three-dimensional projection plus height method to determine the locations of the electromagnetic interference point and the electromagnetic protection point as well as the interference threshold range and the protection threshold range;

[0039] The embodiment of the present invention selects Huangdao District, Qingdao City, Shandong Province as the simulation location. Figure 2As shown, the scene is modeled using a three-dimensional projection plus height method to determine the electromagnetic interference points and electromagnetic protection points, and preset the interference threshold interval and protection threshold interval. In the simulation scene of the embodiment of the present invention, a total of 4 electromagnetic interference points and 3 electromagnetic protection points are determined, as shown in FIG. Figure 3 shown.

[0040] Figure 2 This is a map of the actual geographic location of Huangdao District, Qingdao City, Shandong Province. This scene was chosen for simulation prediction because it is complex, with buildings, vegetation, water, and mountains. This scene contains most of the obstacles likely to be encountered in real-world engineering, making the results of the differential evolution and ray tracing algorithms in this paper more accurate and reliable.

[0041] Figure 3 This is a schematic diagram of simulation modeling of the actual environment. The figure is modeled using three-dimensional projection plus height. The red part in the figure represents the buildings in the simulation environment, the yellow part represents the green belt in the simulation environment, the brown part represents the mountains in the simulation environment, and the blue part represents the lake in the simulation environment. This modeling method can not only speed up the operation efficiency, but also retain the characteristic values ​​of the environment to the greatest extent, so that the error of the simulation results is within an acceptable range.

[0042] The information listed in Table 1 is the simulation point information. The points marked as blue in the table represent interference points that need to be interfered with by electromagnetic interference. The points marked as white represent protection points that need to be protected. These protection points are clearly not inside the building and are not subject to electromagnetic interference. The setting of the protection point can be selected according to the actual situation or can be set freely by the user. Each point has its own location, operating frequency and threshold information. In the example of the present invention, reference can be made to Figure 4 , the blue triangles represent electromagnetic interference points, and the white triangles represent electromagnetic protection points.

[0043] Table 1, Simulation point information list

[0044]

[0045] Step 2: Each electromagnetic shielding device corresponds to an individual in the differential evolution population, initializes the position, power, and frequency parameters of each individual, and sets the key factors in the differential evolution algorithm.

[0046] Initialize the population and set each parameter in the population to a random value. If a parameter is invalid (out of bounds), readjust the parameter until all parameters of the individual are valid. Each individual represents a simulation situation, preparing for the simulation in step 3.

[0047] To make the differential evolution algorithm more efficient and avoid premature convergence, certain algorithm parameters must be determined before starting the algorithm. Generally speaking, the number of individuals in the population should be between 5 and 10 times the number of vector parameters. If the population is too small, it will be difficult to find the optimal solution, while if the population is too large, the calculation time will increase. In this embodiment of the present invention, the X, Y, Z, frequency, and power of the electromagnetic shielding device are used as the number of vector parameters. Therefore, the population size is between 25 and 50 individuals.

[0048] In this step of the embodiment of the present invention, the variation factor F and the crossover probability CR need to be determined. The values ​​of these two parameters will directly affect the accuracy of the algorithm. The embodiment of the present invention adopts an adaptive variation operator.

[0049]

[0050] Among them, F0 represents a fixed value, which is 0.4; λ represents the exponential term; G m Indicates the maximum number of iterations; G indicates the current evolutionary generation.

[0051] Starting from the second generation, the F mutation operator expression is as follows:

[0052]

[0053] Among them, k∈(0,1) is a random number, representing the probability of adjusting the F operator, F u Indicates the upper limit of F value, F l Indicates the lower limit of F value, F u =0.9, F l =0.1.

[0054] The expression of the adaptive CR operator is as follows:

[0055]

[0056] Among them, CR max Indicates the maximum crossover probability, CR min represents the minimum crossover probability.

[0057] Step 3: Take each electromagnetic interference point and each electromagnetic protection point as a simulation point, and each electromagnetic shielding device as a signal source, perform full three-dimensional reverse ray tracing simulation on each individual, and predict the power coverage value of each electromagnetic shielding device at each electromagnetic interference point and each electromagnetic protection point.

[0058] Process the point information in step 1 into the file required by the full three-dimensional reverse ray tracing algorithm, start the simulation, and generate the simulation results.

[0059] The power coverage threshold of each point can be obtained by the following formula:

[0060] P i =P t -L i

[0061] Among them, P i Indicates the power coverage value received by the ith simulation point, P t Indicates the transmission power of the electromagnetic shielding device, L i represents the path loss of the i-th simulation point.

[0062] Step 4, determine whether each power coverage value is within the interference threshold range or the protection threshold range. If so, retain the individual parameters and execute step 5. Otherwise, use the individual's current parameters as the reference point, adjust them in a small range with a certain fluctuation value, and then execute step 3.

[0063] The small-range adjustment of the certain fluctuation value refers to adding a different random value to the X, Y, Z coordinates and power value of the current position of the electromagnetic shielding device respectively. The value of each random value cannot exceed the boundary value of the modified parameter. If the modified parameter value exceeds its corresponding boundary value, a new random value is selected and the parameter is modified again until the parameter value of the parameter is modified to be within its corresponding boundary.

[0064] The power coverage value of each point obtained according to the simulation is compared with the interference threshold interval and protection threshold interval preset in the example of the present invention. If the simulated power coverage values ​​obtained at all simulation points are within their corresponding intervals, the individual is retained; otherwise, each parameter of the individual is adjusted, and simulation and comparison are performed again until the algorithm iteration is completed.

[0065] Step 5: Calculate the fitness function value of each retained individual, and select the function value closest to 0 from all fitness function values ​​as the best individual to set the position, power, and frequency parameters of the electromagnetic shielding.

[0066] The fitness function is as follows:

[0067]

[0068] Among them, F h represents the fitness value of the hth retained individual, k b represents the interference weight factor, p bsi represents the power coverage value obtained by full three-dimensional reverse ray tracing algorithm simulation at the i-th electromagnetic interference point, p bi Indicates the i The interference threshold power of the electromagnetic interference point, i = 1, 2, ... n, n represents the total number of electromagnetic interference points, k w represents the protection weight factor, p wsjrepresents the power coverage value obtained by simulating the full three-dimensional reverse ray tracing algorithm at the jth electromagnetic protection point, p wi k represents the protection threshold power of the jth electromagnetic protection point, j = 1, 2, ... m, m represents the total number of electromagnetic protection points. b and k w The value of is selected in the range of (0, 20] to ensure that the result of each item is greater than or equal to 0.

[0069] In the embodiment of the present invention, k b Take 3, k w Take 1.2. When the algorithm ends, calculate the fitness function value of the retained individual. The smaller the fitness function value, the better. If the fitness value of the best individual is close to 0, it is considered that the algorithm has found a feasible solution. The parameters of the corresponding electromagnetic shielding device can be adjusted according to the parameters of the best individual.

[0070] In the embodiment of the present invention, a total of 22 simulations were performed, and the simulation results are shown in Table 2. Each simulation met the actual requirements, indicating that the algorithm is very robust and suitable for setting the parameters of the electromagnetic shielding device.

[0071] The effect of the present invention can be further demonstrated through the following simulation.

[0072] 1. Simulation experiment conditions.

[0073] The software platforms for the simulation experiment of the present invention are: Windows 11 operating system, Pycharm2023.3.2 and Python3.11.

[0074] The simulation data is a simulation of the electromagnetic interference points and electromagnetic protection points preset in Huangdao District, Qingdao City, Shandong Province. The present invention presets a total of 4 electromagnetic interference points and 3 electromagnetic protection points. Table 1 shows the specific information of each point. Figure 2 , Figure 3 They are the actual scene and modeling scene in Huangdao District, Qingdao City, Shandong Province respectively.

[0075] 2. Analysis of simulation content and results.

[0076] The simulation experiment of the present invention adopts the method of the present invention and the existing technology to simulate the electromagnetic interference point and the electromagnetic protection point in the simulation scene 22 times. The simulation experiment process and results are shown in the figure. Figure 5 、 Figure 6 、 Figure 7 shown.

[0077] Figure 5 and Figure 6 It represents the changing trend of the best individual fitness function value of the population and the average fitness function value of the population individuals in each simulation process. Figure 7This is a schematic diagram of the position results of a group of electromagnetic shielding devices after the simulation experiment of the present invention is iterated based on differential evolution and ray tracing algorithm.

[0078] The existing technologies used in the simulation experiments are:

[0079] Xidian University proposed an efficient electromagnetic simulation method for outdoor scenes in its patent application document "A method, device and application of an outdoor fast ray tracing model" (application number: CN202211304721.2, application publication number: CN115690352A).

[0080] The following combination Figure 5 and Figure 6 The fitness function change diagram further illustrates the effect of the present invention.

[0081] Figure 5 and Figure 6 The chart shows the changing trends of the average fitness value of the individuals in the population and the fitness value of the best individual in the population during the 22 algorithm iterations. The horizontal axis represents the number of iterations the algorithm is going through, and the vertical axis represents the fitness function value. Figure 5 It can be seen that the average fitness function value of the population individuals decreases with the increase of the number of iterations. Figure 6 It can be seen that the fitness function value of the best individual in the population continues to decrease with the increase in the number of iterations, and eventually approaches or equals 0, which is in line with expectations. Table 2 shows the results of 22 simulations, and it can be seen that each simulation result meets the requirements.

[0082] Table 2 Simulation results

[0083]

[0084] refer to Figure 7 , select a set of simulation results, the red triangle represents the placement position of the electromagnetic shielding device, each red triangle corresponds to an electromagnetic shielding device, place the electromagnetic shielding device at that position, and set the power and frequency of the electromagnetic shielding according to the optimal individual parameters obtained by the algorithm, you can achieve efficient, accurate, and multi-frequency electromagnetic interference effects.

[0085] The above simulation experiments demonstrate that the present invention, based on an algorithm combining differential evolution and ray tracing, can simulate preset electromagnetic interference points and electromagnetic protection points in the simulation scenario to obtain the optimal population individual, thereby rationally setting the various parameters of the electromagnetic shielding device based on the parameters of the optimal individual. This solves the problem of existing electromagnetic shielding devices being unable to distinguish between electromagnetic interference points and electromagnetic protection points, as well as the problem of multiple frequencies. It provides a method for adjusting electromagnetic shielding device parameters in complex situations.

Claims

1. A parameter optimization method for electromagnetic shielding device based on differential evolution and ray tracing algorithm, characterized in that: A full three-dimensional reverse ray tracing algorithm is used to predict the power coverage value of the electromagnetic shielding device. A method combining differential evolution and ray tracing is used to optimize the frequency, power, and position parameters of the simulated individuals. The steps of this parameter optimization method include the following: Step 1: Use 3D projection plus height to model the simulation scene, determine the locations of electromagnetic interference points and electromagnetic protection points, as well as the interference threshold range and protection threshold range; Step 2: Each electromagnetic shielding device corresponds to an individual in the differential evolution population, initializes the position, power, and frequency parameters of each individual, and sets the key factors in the differential evolution algorithm; Step 3: Treat each electromagnetic interference point and each electromagnetic protection point as a simulation point, treat each electromagnetic shielding device as a signal source, perform full three-dimensional reverse ray tracing simulation on each individual, and predict the power coverage value of each electromagnetic shielding device at each electromagnetic interference point and each electromagnetic protection point; Step 4: Determine whether each power coverage value falls within the interference threshold interval or the protection threshold interval. If so, retain the individual parameters and execute step 5. Otherwise, use the individual's current parameters as a reference point, make small adjustments within a certain fluctuation value, and then execute step 3. Step 5: Calculate the fitness function value of each retained individual, select the function value closest to 0 from all fitness function values ​​as the best individual, and set the position, power, and frequency parameters of the electromagnetic shielding accordingly.

2. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The method of using three-dimensional projection plus height to model the simulation scene described in step 1 means starting from any vertex of the polygon corresponding to the top view of the obstacle to be modeled in the simulation scene, recording all vertices in a clockwise direction, connecting two adjacent vertices to represent an edge of the top view, and specifying a height for each polygon in the top view, finally forming a cylinder to complete the modeling of the entire scene.

3. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The electromagnetic interference point position in step 1 refers to the positions of multiple interference signal points emitted by a preset electromagnetic shielding device in the scene to be simulated according to user needs. Each interference signal point cannot coincide with an electromagnetic protection point.

4. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The electromagnetic protection point positions in step 1 refer to multiple protection points preset in the simulation scene according to user needs that are not interfered by the interference signal emitted by the electromagnetic shielding device. Each protection point cannot overlap with the electromagnetic interference point.

5. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The interference threshold interval in step 1 refers to an independent power interval preset for each electromagnetic interference point. The power interval range is set by the user according to actual needs. When the interference signal power value received by the electromagnetic interference point falls within the interval, the point is considered to have been interfered with.

6. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The protection threshold interval in step 1 refers to an independent power interval preset for each electromagnetic protection point. The power interval range is set by the user according to actual needs. When the signal power value received by the electromagnetic protection point is within the interval, it is considered that the point is not interfered with.

7. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1, characterized in that: The steps for performing a full 3D reverse ray tracing simulation for each individual in step 3 are as follows: The first step is to process the preset electromagnetic interference points and electromagnetic protection points into simulation points for full three-dimensional reverse ray tracing; In the second step, each electromagnetic shielding device is regarded as a signal source, and full three-dimensional reverse ray tracing is used to simulate the simulation points in the scene to be simulated.

8. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The power coverage value described in step 3 refers to the power of the interference signal emitted by the electromagnetic shielding device minus the path loss corresponding to each simulation point, which can be used to obtain the power coverage value of each electromagnetic interference point and each electromagnetic protection point. Its expression is as follows: P i =P t -L i Among them, P i Indicates the power coverage value received by the ith simulation point, P t Indicates the transmission power of the electromagnetic shielding device, L i represents the path loss of the i-th simulation point.

9. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1, characterized in that: The small-range adjustment of the certain fluctuation value described in step 4 refers to adding a different random value to the X, Y, Z coordinates and power values ​​of the current position of the electromagnetic shielding device, and the value of each random value is less than the boundary value of the modified parameter. If the modified parameter value exceeds its corresponding boundary value, a new random value is selected and the fluctuation value of the parameter is adjusted in a small range again until the adjusted parameter value is within its corresponding boundary.

10. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1, characterized in that: The fitness function value of each retained individual calculated in step 5 is obtained by the following formula: Among them, F h represents the fitness value of the hth retained individual, k b represents the interference weight factor, p bsi represents the power coverage value obtained by full three-dimensional reverse ray tracing algorithm simulation at the i-th electromagnetic interference point, p bi Indicates the i The interference threshold power of the electromagnetic interference point, i = 1, 2, ... n, n represents the total number of electromagnetic interference points, k w represents the protection weight factor, p wsj represents the power coverage value obtained by simulating the full three-dimensional reverse ray tracing algorithm at the jth electromagnetic protection point, p wi represents the protection threshold power of the jth electromagnetic protection point, j = 1, 2, ... m, m represents the total number of electromagnetic protection points; k b and k w The value of is selected in the range of (0, 20] to ensure that the result of each item is greater than or equal to 0.

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