Electromagnetic shielding instrument parameter optimization method based on differential evolution and ray tracing algorithm

Abstract

The invention discloses an electromagnetic shielding instrument parameter optimization method based on differential evolution and a ray tracing algorithm, and the method comprises the implementation steps: modeling a to-be-simulated scene in a three-dimensional projection and height mode, and presetting an electromagnetic interference point, a protection point and related information; enabling the electromagnetic shielding instrument to correspond to population individuals in a differential evolution algorithm, initializing individual parameters, and setting key factors of differential evolution; simulating the simulation points by using a full-three-dimensional reverse ray tracing algorithm, and retaining or adjusting individual parameters according to a result; and selecting an optimal individual from the reserved individuals, and adjusting the power, the frequency and the position of the electromagnetic shielding instrument by using parameters of the optimal individual. The method effectively solves the problem that interference points and protection points are difficult to distinguish and multiple frequency points are difficult to distinguish in electromagnetic interference, avoids accidental damage caused by interference, and can more efficiently optimize parameters of the electromagnetic shielding instrument according to actual scenes.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and further relates to a method for optimizing electromagnetic shielding device parameters based on differential evolution and ray tracing algorithm in the field of radio wave propagation prediction model modeling and optimization technology. The present invention can be used to provide an interference decision for specific frequency points and specific areas in a complex environment, so as to adjust various parameters of the electromagnetic shielding device. Background Art

[0002] Electromagnetic shielding devices are used in more and more security scenarios. Electromagnetic security control refers to the preset interference of specific frequency points and specific areas. Common scenarios such as signal shielding devices in examination rooms transmit interference signals of the entire frequency band by scanning the entire frequency band. For example, the effective signal emitted by electronic products such as mobile phones is distorted and cannot be resolved by the base station to achieve the purpose of signal shielding. However, this traditional method is prone to false interference in actual use because it cannot distinguish between effective signals and signals that need to be interfered with. And because the actual application scenarios are complex, if the power of the signal shielding device is simply increased to force some malicious signals to be distorted, it will not only affect the propagation effect of radio waves, but also be costly and unable to transmit effective interference signals for fixed-point specific interference areas. Therefore, it is particularly important to provide an optimal interference decision for specific frequency points and specific areas in complex environments, so as to adjust the various parameters of the electromagnetic shielding device and achieve targeted signal shielding.

[0003] Xidian University disclosed a method for adjusting jammer parameters by using multi-target jammer decision-making in its patent application "A multi-target jammer 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 jammer decision 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 jammer decision model; (3) implementing the MOPSO optimization algorithm to optimize the jammer decision objective function. The optimization result is the jammer station layout result; (4) selecting solutions with different tendencies for the multiple results of step 3, and selecting a tendentious Pareto solution according to the task requirements. Although this method can achieve uniform 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 copes 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) analysis and parameter initialization of the suppression task 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 coordinated 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: by calculating the received signal strength at the suppression typical point or specific target, the suppression effect of the coordinated suppression of various suppression devices is measured; (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 coordinated suppression frequency: constructing a linear programming problem on coordinated power optimization, and using the large M simplex method to solve the linear programming problem to obtain the optimal coordinated suppression power; (6) evaluating the suppression effect of the electromagnetic suppression area, checking the blocking of 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 effects with multiple frequencies, high efficiency and low accidental damage. However, this method still has the following shortcomings: This method proposes electromagnetic suppression with multiple frequencies, which can solve the problem brought by the frequency band, but does not consider the possibility of moving the interfering device and ignores the portability of the device, which will result 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 deficiencies of the above-mentioned prior art 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 accurate and efficient electromagnetic suppression and protection at a fixed point by adjusting the electromagnetic shielding device parameters in a complex environment.

[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 regarded 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 and the protection threshold, the parameters of each individual such as frequency, power, and position information are continuously optimized. This solves the problem that the prior art cannot suppress interference at multiple frequency points at the same time. For the genetic algorithm and simulated annealing algorithm for traditional multi-target interference decision-making, premature maturity and falling into the local optimal solution will occur in each population iteration process, and the commonly used forward ray tracing algorithm will track a large number of rays and waste 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 a signal source, and taking the interfered points and protection points as simulation points. 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 error problem caused by the internal limitations of the algorithm in a specific urban environment.

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

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

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

[0010] Step 3, taking each electromagnetic interference point and each electromagnetic protection point as a simulation point, taking each electromagnetic shielding device as a signal source, performing full three-dimensional reverse ray tracing simulation on each individual, and predicting 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 interval or the protection threshold interval. If so, retain the parameters of the individual and then execute step 5. Otherwise, take the current parameters of the individual as the reference point, adjust them within a small range with a certain fluctuation value, and then execute step 3.

[0012] 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 to set the position, power, and frequency parameters of the electromagnetic shielding.

[0013] Furthermore, the use of the three-dimensional projection plus height method to model the scene to be simulated refers to 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 scene to be simulated according to user needs, which 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, not 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.

[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, not 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 for each individual refers to 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 represents 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 to be 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 of the jth electromagnetic protection point obtained by full three-dimensional reverse ray tracing algorithm simulation, 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 a signal source, and takes the interfered point and the protection point as simulation points, and simulates and predicts the power coverage of the electromagnetic shielding device, thereby overcoming the problem of slow simulation efficiency in the prior art. The present invention can accurately achieve multi-frequency and multi-point suppression effects, and 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 with the differential evolution algorithm, which not only avoids premature phenomenon, improves 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 be used in more complex scenarios. By adjusting the parameters of the electromagnetic shielding device, it can suppress the interference electromagnetic at a fixed point, accurately and efficiently, and 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 A schematic diagram of the distribution of electromagnetic interference points and electromagnetic protection points according to an embodiment of the present invention;

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

[0035] Figure 7 It is a schematic diagram of a group of electromagnetic shielding device position results 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, using a three-dimensional projection plus height method to model the simulation scene of the embodiment of the present invention, determine the locations of the electromagnetic interference points and the electromagnetic protection points, as well as the interference threshold interval and the protection threshold interval;

[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, the electromagnetic interference point and the electromagnetic protection point are determined, and the interference threshold interval and the protection threshold interval are preset. 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 real-world map of the geographical location of Huangdao District, Qingdao City, Shandong Province. This scene is selected for simulation prediction because the actual situation of the scene is relatively complex, with not only buildings, vegetation, water, but also mountains. This scene contains most of the obstacles that may be encountered in the actual engineering field, making the accuracy of the results of the differential evolution and ray tracing algorithm of the present invention more realistic and reliable.

[0041] Figure 3 This is a schematic diagram of simulation modeling of the actual environment. The figure is modeled by 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 belts in the simulation environment, the brown part represents the mountains in the simulation environment, and the blue part represents the lakes in the simulation environment. This modeling method can not only speed up the operation efficiency, but also retain the characteristic values ​​in 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 defined by the user as 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 it can be freely set 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, list of simulation point information

[0044]

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

[0046] Initialize the population and set each parameter in the population individual to a random value. If a parameter is invalid (outside the boundary value), 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] In order to make the differential evolution algorithm more efficient and avoid premature phenomenon, some parameters of the algorithm need to be determined before the algorithm is started. Generally speaking, the number of individuals in the population is between 5 and 10 times the number of vector parameters. If the population is too small, it is difficult to search for the optimal solution. If the population is too large, the calculation time will increase. In the 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 individuals are in the range of 25-50.

[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 an exponential term; G m represents the maximum number of iterations; G represents 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 Represents the maximum value of the 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, take 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 represents 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 parameters of the individual and execute step 5. Otherwise, take the current parameters of the individual as the reference point, adjust them in a small range with a certain fluctuation value, and then execute step 3.

[0063] The certain fluctuation value is adjusted in a small range, which means that a different random value is added 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 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 by 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, 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 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 of the jth electromagnetic protection point obtained by full three-dimensional reverse ray tracing algorithm simulation, 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 are performed, and the simulation results are shown in Table 2. Each simulation meets 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 experimental conditions.

[0073] The software platforms for the simulation experiment of the present invention are: Windows 11 operating system, Pycharm 2023.3.2, and Python 3.11.

[0074] The data of the simulation experiment is a simulation of the electromagnetic interference points and electromagnetic protection points preset in Huangdao District, Qingdao City, Shandong Province. The present invention presets 4 electromagnetic interference points and 3 electromagnetic protection points, and 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 prior art 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 FIG. Figure 5 , Figure 6 , Figure 7 shown.

[0077] Figure 5 and Figure 6 It represents the changing trend of the average fitness function value of the individuals in the population and the fitness function value of the best individual in the population during each simulation process. Figure 7It is a schematic diagram of a group of electromagnetic shielding device position results 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 experiment 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] Combine the following Figure 5 and Figure 6 The fitness function change diagram further describes the effect of the present invention.

[0081] Figure 5 and Figure 6 The average fitness value of the population and the fitness value of the best individual in the population during the 22 algorithm iterations are shown. 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 decreases with the increase of iteration times, and finally approaches 0 or equals 0, which is in line with the expected situation. 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 indicates the placement position of the electromagnetic shielding device, each red triangle corresponds to an electromagnetic shielding device, place the electromagnetic shielding device at this 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 show that the algorithm based on differential evolution and ray tracing can simulate the preset electromagnetic interference points and electromagnetic protection points in the simulation scene to obtain the best population individual, so as to reasonably set the various parameters of the electromagnetic shielding device according to the parameters of the best individual. It solves the problem that the existing electromagnetic shielding device cannot distinguish between electromagnetic interference points and electromagnetic protection points and multiple frequencies. It is a method for adjusting the parameters of the electromagnetic shielding device in complex situations.

Claims

1. A method for optimizing electromagnetic shielding device parameters based on differential evolution and ray tracing algorithm, characterized in that: The power coverage value of the electromagnetic shielding device is predicted using a full three-dimensional reverse ray tracing algorithm. The frequency, power, and position parameters of the simulated individuals are optimized using a combination of differential evolution and ray tracing. The steps of the parameter optimization method include the following: Step 1: Use three-dimensional projection plus height to model the simulation scene, determine the locations of electromagnetic interference points and electromagnetic protection points, as well as interference threshold intervals and protection threshold intervals; Step 2, each electromagnetic shielding device corresponds to an individual in the differential evolution population, the position, power, and frequency parameters of each individual are initialized, and the key factors in the differential evolution algorithm are set; Step 3, taking each electromagnetic interference point and each electromagnetic protection point as a simulation point, taking each electromagnetic shielding device as a signal source, performing full three-dimensional reverse ray tracing simulation on each individual, and predicting 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 parameters of the individual and then execute step 5. Otherwise, take the current parameters of the individual as the reference point, adjust them within a small range with 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 use of three-dimensional projection plus height method in step 1 to model the simulation scene 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, and each interference signal point cannot overlap 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 position in step 1 refers to a plurality of protection points preset in the scene to be simulated that are not interfered by the interference signal emitted by the electromagnetic shielding device according to user needs, and 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.

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.

7. The electromagnetic shielding device parameter optimization method based on differential evolution and ray tracing algorithm according to claim 1 is characterized in that: The steps for performing 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 the simulation points are simulated in the scene to be simulated using full three-dimensional reverse ray tracing.

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 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 represents 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 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 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 of the jth electromagnetic protection point obtained by full three-dimensional reverse ray tracing algorithm simulation, 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.

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