Methods and devices for simulating electromagnetic signals in complex multi-regional natural environments

Abstract

This invention provides a method and apparatus for simulating electromagnetic signals in complex multi-regional natural environments. The method includes: acquiring characteristic parameters of the complex multi-regional natural environment; performing spatial discretization and numerical calculation using the DGTD and PE methods to obtain electromagnetic interference propagation characteristic data for each region; obtaining the transfer function of different regions using the Discrete Laplace Transform; cascading the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region; using a LabVIEW program to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region to obtain an output signal; and using an NI and a radial hardware-in-the-loop simulation device to simulate the output signal to obtain the simulated electromagnetic signals of the complex multi-regional natural environment. The electromagnetic signal simulation method established by this invention for complex natural environments can accurately simulate the real electromagnetic environment of the field, solving the problem of indoor simulation equivalently replacing field tests in environments with complex structural obstacles.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic signal simulation technology, and in particular to a method and apparatus for simulating electromagnetic signals in complex multi-regional natural environments. Background Technology

[0002] With the continuous development of electronic information technology, more and more electrical and electronic equipment are being widely used in complex systems such as aircraft, ships, and rail transit trains. Currently, the common methods for studying the electromagnetic effects and anti-interference performance of equipment mainly include all-digital simulation and field testing. All-digital simulation technology has advantages such as all-weather operation, multi-scenario capability, and low cost. However, it cannot reflect the complex characteristics of the system beyond the mathematical model, especially the problems of internal circuit coupling and multi-physics field effects, which are difficult to accurately simulate. In addition, it cannot comprehensively complete the integration and verification of electrical systems. As for field testing, although it can reproduce the real scene to the greatest extent, the testing costs in terms of manpower and material resources are high. In addition, field testing makes it difficult to switch scenes at any time, resulting in low flexibility. In contrast, hardware-in-the-loop (HIL) simulation technology, with its combination of "virtual" and "physical," retains the flexibility of all-digital simulation while also integrating the real reliability of physical hardware in field testing.

[0003] However, in typical experimental environments, interference signals are simulated output via signal generators, often neglecting the influence of the environment. For example, environmental factors such as atmospheric conditions, terrain, soil, and complex structural obstacles along the propagation path can all affect electromagnetic interference propagation. These influences on interference signal prediction are real and place higher demands on hardware-in-the-loop (HIL) simulations. Therefore, utilizing digital simulation to comprehensively and accurately simulate the real electromagnetic environment of an external field is crucial for equivalent substitution experiments.

[0004] Therefore, there is an urgent need for a method to simulate electromagnetic signals in complex natural environments. Summary of the Invention

[0005] The embodiments of the present invention provide a method and apparatus for simulating electromagnetic signals in complex multi-regional natural environments, so as to effectively use indoor simulation to replace field tests in environments with complex structural obstacles.

[0006] To achieve the above objectives, the present invention adopts the following technical solution.

[0007] According to one aspect of the present invention, a method for simulating electromagnetic signals in complex multi-regional natural environments is provided, comprising:

[0008] The topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments are obtained. Based on these characteristics, the time-domain discontinuous Galilean-parabolic DGTD method and the parabolic equation PE method are used for spatial discretization and numerical calculation to obtain electromagnetic disturbance propagation characteristics data for each region.

[0009] Based on the electromagnetic interference propagation characteristics data of each region, the input electromagnetic signal and the output electromagnetic signal, the transfer function of different regions is obtained by using the discrete Laplace transform. The transfer functions of each region are cascaded to obtain the transfer function of the entire electromagnetic interference propagation region.

[0010] Based on the transfer function of the entire electromagnetic interference propagation area, the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation area are mixed using the LabVIEW program to obtain the output signal. The output signal is then simulated using the virtual instrument NI and a radiation-type hardware-in-the-loop simulation device to obtain the simulated electromagnetic signals of the complex multi-regional natural environment.

[0011] Preferably, the step of obtaining topographic, geomorphological, and meteorological characteristic parameters of complex multi-regional natural environments, and using the DGTD and PE methods to perform spatial discretization and numerical calculations based on the characteristic parameters to obtain electromagnetic interference propagation characteristic data for each region, includes:

[0012] The topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments are obtained, and spatial discretization and numerical calculation are performed using the DGTD and PE methods based on the obtained characteristics.

[0013] For flat terrain, the split-step Fourier transform (SSFT-PE) method is used to calculate the propagation process of electromagnetic waves and predict the propagation characteristics of electromagnetic disturbances in flat terrain.

[0014] For complex terrain and rough surfaces, the alternating direction implicit ADI-PE method is used to calculate the propagation characteristics of electromagnetic disturbances;

[0015] Calculate the time-domain signal near the obstacle as the output signal of the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacle.

[0016] Output electromagnetic interference propagation characteristic data for each region. This data includes the frequency, intensity, waveform, propagation path, and phase information of the interference signal, as well as the time-domain signal near the obstacle. Preferably, the step of obtaining the transfer function of different regions using the discrete Laplace transform based on the electromagnetic interference propagation characteristic data, the input electromagnetic signal, and the output electromagnetic signal, and then cascading the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region, includes:

[0017] Assuming a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal:

[0018]

[0019] In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c Center frequency

[0020] The propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method. The time-domain signal near the obstacle is then obtained and used as the output signal y in the TDPE region. PE Using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG Based on the input and output signals of each region, the transfer function of each region is obtained by using the discrete Laplace transform. The transfer functions of different regions are cascaded to obtain the transfer function H(z) of the entire electromagnetic interference propagation region.

[0021] After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.:

[0022] y(t)=x(t)*h(t) (2)

[0023] The transfer function of the TDPE region is expressed as:

[0024]

[0025] In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively, x(z) and y(z). PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation.

[0026] Assuming the distance between the obstacles is large enough to ignore multiple scattering between them, T1(z) and T2(z) are the system transfer functions of the two multi-scale obstacles, respectively:

[0027]

[0028] T DG (z) is the transfer function of the DGTD region, x(z) and y DG (z) represent the input and output discrete-time signals x(k) and y(k) of the DGTD region, respectively. DG (k) The result after Z-transformation;

[0029] If there is mutual coupling between obstacles, the DGTD method can be used to solve for the backscattering of the obstacles.

[0030] Preferably, the step of using a LabVIEW program to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region based on the transfer function of the entire electromagnetic interference propagation region to obtain an output signal, and then using an NI virtual instrument and a radiation-based hardware-in-the-loop simulation device to simulate and process the output signal to obtain the simulated electromagnetic signals of the complex multi-regional natural environment, includes:

[0031] Based on the transfer function of the entire electromagnetic interference propagation area, the original electromagnetic signal of the entire electromagnetic interference propagation area and the characteristic parameters of the complex natural environment are mixed using the LABVIEW program to obtain the output signal. The output signal is then processed by the NI virtual instrument to output the simulated electromagnetic signal.

[0032] The electromagnetic signals simulated by the radiation are processed by the power amplifier and the transmitting antenna to achieve radiation electromagnetic effect simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

[0033] According to another aspect of the present invention, an electromagnetic signal simulation device for complex multi-region natural environments is provided, comprising: a first calculation module, a second calculation module and a third calculation module;

[0034] The first calculation module acquires the topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments. Based on these characteristics, it uses the time-domain discontinuous Galerkin-parabolic DGTD method and the parabolic equation PE method to perform spatial discretization and numerical calculations, thereby acquiring electromagnetic disturbance propagation characteristic data for each region.

[0035] The second calculation module obtains the transfer function of different regions based on the electromagnetic interference propagation characteristic data of each region, the input electromagnetic signal and the output electromagnetic signal, and cascades the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region.

[0036] The third calculation module uses a LabVIEW program to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region based on the transfer function of the entire electromagnetic interference propagation region to obtain an output signal. The output signal is then simulated using NI virtual instruments and a radiation-type hardware-in-the-loop simulation device to obtain the simulated electromagnetic signals of the complex multi-regional natural environment.

[0037] Preferably, the first calculation module is specifically used to acquire the topographic, geomorphological and meteorological condition characteristic parameters of complex multi-regional natural environments, and to perform spatial discretization and numerical calculation using the DGTD method and PE method based on the acquired characteristic parameters;

[0038] For flat terrain, the split-step Fourier transform (SSFT-PE) method is used to calculate the propagation process of electromagnetic waves and predict the propagation characteristics of electromagnetic disturbances in flat terrain.

[0039] For complex terrain and rough surfaces, the alternating direction implicit ADI-PE method is used to calculate the propagation characteristics of electromagnetic disturbances;

[0040] Calculate the time-domain signal near the obstacle as the output signal of the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacle.

[0041] The system outputs electromagnetic interference propagation characteristic data for each region. This data includes the frequency, intensity, waveform, propagation path, and phase information of the interference signal, as well as the time-domain signal near the obstacle. Preferably, the second calculation module is specifically used to obtain the transfer function of different regions using the discrete Laplace transform based on the electromagnetic interference propagation characteristic data, the input electromagnetic signal, and the output electromagnetic signal. The transfer functions of each region are then cascaded to obtain the transfer function of the entire electromagnetic interference propagation region, including:

[0042] Assuming a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal:

[0043]

[0044] In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c Center frequency

[0045] The propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method. The time-domain signal near the obstacle is then obtained and used as the output signal y in the TDPE region. PE Using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG Based on the input and output signals of each region, the transfer function of each region is obtained by using the discrete Laplace transform. The transfer functions of different regions are cascaded to obtain the transfer function H(z) of the entire electromagnetic interference propagation region.

[0046] After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.:

[0047] y(t)=x(t)*h(t) (2)

[0048] The transfer function of the TDPE region is expressed as:

[0049]

[0050] In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively, x(z) and y(z). PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation.

[0051] Assuming the distance between the obstacles is large enough to ignore multiple scattering between them, T1(z) and T2(z) are the system transfer functions of the two multi-scale obstacles, respectively:

[0052]

[0053] T DG (z) is the transfer function of the DGTD region, x(z) and y DG (z) represent the input and output discrete-time signals x(k) and y(k) of the DGTD region, respectively. DG (k) The result after Z-transformation;

[0054] If there is mutual coupling between obstacles, the DGTD method can be used to solve for the backscattering of the obstacles.

[0055] Preferably, the third calculation module is specifically used to use a LabVIEW program to mix the original electromagnetic signal of the entire electromagnetic interference propagation area and the characteristic parameters of the complex natural environment according to the transfer function of the entire electromagnetic interference propagation area, to obtain an output signal, and to perform simulated data processing on the output signal through NI virtual instruments to output a simulated electromagnetic signal.

[0056] The electromagnetic signals simulated by the radiation are processed by the power amplifier and the transmitting antenna to achieve radiation electromagnetic effect simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

[0057] According to another aspect of the present invention, a computer device is provided, comprising:

[0058] The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes these computer instructions to perform the electromagnetic signal simulation method for complex multi-regional natural environments.

[0059] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein computer instructions are stored on the computer storage medium for causing a computer to execute the electromagnetic signal simulation method for complex multi-regional natural environments.

[0060] As can be seen from the technical solutions provided by the embodiments of the present invention above, the electromagnetic signal simulation in complex natural environments finally established by the present invention can accurately simulate the real electromagnetic environment of the external field, and solve the problem of equivalent replacement of indoor simulation with external field tests in environments with complex structural obstacles.

[0061] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of the invention. Attached Figure Description

[0062] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 This is a flowchart illustrating an electromagnetic signal simulation method under a complex natural environment according to an embodiment of the present invention.

[0064] Figure 2 This is a flowchart illustrating another electromagnetic signal simulation method under complex natural environments according to an embodiment of the present invention.

[0065] Figure 3 This is a flowchart illustrating another electromagnetic signal simulation method under complex natural environments according to an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram of a method for constructing the electromagnetic signal propagation region transfer function based on the discrete Laplace transform according to an embodiment of the present invention;

[0067] Figure 5 This is a schematic diagram of region transfer function extraction according to an embodiment of the present invention;

[0068] Figure 6 This is a schematic diagram of an electromagnetic signal simulation method under complex natural environments according to an embodiment of the present invention;

[0069] Figure 7 This is a schematic diagram of a multi-region segmentation surface according to an embodiment of the present invention;

[0070] Figure 8This is a structural diagram of an electromagnetic signal simulation device for a complex multi-regional natural environment according to an embodiment of the present invention;

[0071] Figure 9 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0072] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0073] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or couplings. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items.

[0074] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0075] To facilitate understanding of the embodiments of the present invention, the following will provide further explanation and description with reference to the accompanying drawings and several specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0076] Researching and analyzing the impact of environmental factors such as atmospheric medium, topography, soil, and complex structural obstacles in the propagation path on electromagnetic interference propagation is one of the keys to solving the problem of equivalent substitution for field tests. Therefore, this invention provides a method for simulating electromagnetic signals in complex natural environments, which can solve the problem of indoor simulation equivalent substitution for field tests in environments with complex structural obstacles.

[0077] This embodiment provides a simulation method for electromagnetic environment effects under different environments, which can be used in servers, such as desktop computers and tablets. A flowchart of a method for simulating electromagnetic signals under complex natural environments provided by this embodiment is shown below. Figure 1 As shown, the process includes the following steps:

[0078] Step S101: Based on the DGTD (Discontinuous Galerkin Time Domain) equation, predict the propagation characteristics of electromagnetic disturbances in complex multi-regional natural environments.

[0079] The system acquires characteristic parameters of complex multi-regional natural environments, such as topography, geomorphology, and meteorological conditions. Based on the acquired characteristic parameters, it uses the DGTD method and the PE (Parabolic Equation) method (including SSFT (Spit-step Fourier Transform)-PE and ADI (Alternating Direction Implicit)-PE) to perform spatial discretization and numerical calculation.

[0080] For flat terrain, the SSFT-PE method is used to calculate the propagation process of electromagnetic waves.

[0081] For complex terrain and rough surfaces, the ADI-PE method is used to improve numerical accuracy.

[0082] Calculate the time-domain signal near the obstacle as the output signal for the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacles.

[0083] Finally, the electromagnetic interference propagation characteristic data for each region is output. This data includes information such as the frequency, intensity, waveform, propagation path, and phase of the interference signal, as well as time-domain signals near obstacles. This data serves as input for subsequent steps. Step S102: Construct the electromagnetic signal propagation region transfer function based on the discrete Laplace transform.

[0084] Based on the electromagnetic interference propagation characteristics data, input electromagnetic signals, and output electromagnetic signals of each region, the transfer functions of different regions are obtained using the discrete Laplace transform. The transfer functions of each region are then cascaded to obtain the transfer function of the entire electromagnetic interference propagation region.

[0085] If necessary, the system transfer function coefficients can be quickly solved using the system identification module in the Matlab simulation software.

[0086] Step S103: A method and apparatus for simulating electromagnetic signals in complex natural environments based on NI (National Instruments, virtual instruments).

[0087] Based on the transfer function of the entire electromagnetic interference propagation region, the original electromagnetic signals (such as sinusoidal modulated Gaussian pulse signals) and characteristic parameters of the complex natural environment of the entire electromagnetic interference propagation region are mixed using the LabVIEW program to obtain the output signal. The output signal is then processed using NI virtual instruments to output a simulated electromagnetic signal.

[0088] By using a radiation-type hardware-in-the-loop simulation device, the electromagnetic signals simulated above are processed through a power amplifier and a transmitting antenna to achieve radiation electromagnetic effect hardware-in-the-loop simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

[0089] Figure 2 Yes Figure 1 A detailed breakdown of steps S101 and S102 is provided below. Figure 3 Yes Figure 1 Detailed implementation steps of step S103.

[0090] Specifically, step S101 includes the following: DGTD is a time-domain numerical computation method belonging to the same category as the Finite-Difference Time-Domain (FETD) method. The spatial discretization of the DGTD method shares the same characteristics as the FETD method. Both methods use unstructured meshes to achieve spatial discretization of the computational domain. Unstructured meshes have the advantage of better fitting effects on curved surfaces and complex structures, while avoiding the approximation error problem that exists when using orthogonal meshes in the FDTD method. Another feature of the DGTD method is the use of numerical flux from the Finite-Difference Time-Domain (FDTD) method. This method can relax the constraint on the tangential continuity of the electromagnetic field, which is beneficial for achieving domain decomposition and parallel computation. Furthermore, compared to the problem of the huge dimension of the global system matrix in the traditional FETD method, the DGTD method has a much smaller computational cost for inverting the element matrix than FETD, and its handling of time-domain step-by-step solutions between adjacent elements has characteristics similar to the Finite-Difference Time-Domain (FDTD). DGTD is based on Maxwell's curl equations, while FETD is based on the electromagnetic wave equations for discretization. Therefore, the explicit electromagnetic field alternating step scheme of DGTD requires less computation in solving the global system matrix in each step compared to the FETD method. In summary, the DGTD method combines the advantages of both FETD and FDTD while avoiding their respective disadvantages, making it a cutting-edge method for calculating scattering problems in multi-scale and dispersive media.

[0091] The PE method is derived by approximating Maxwell's wave equations. Compared to high-frequency approximation algorithms, the parabolic equation method fully considers the effects of electromagnetic wave refraction and diffraction, and also handles the refractive index term to account for environmental effects such as complex geographical and meteorological environments. Compared to full-wave numerical methods, the biggest advantage of the split-step Fourier transform (SSFT) solution in the parabolic equation method is that the electromagnetic wave wavelength has little influence on the iteration step length. This characteristic makes the algorithm more efficient and consumes less memory. Therefore, the parabolic equation method is adopted as the calculation method for electromagnetic disturbance propagation in large-area complex environments.

[0092] However, for boundary problems such as rough surfaces, large mesh sizes can lead to errors in SSFT-PE, while the Alternating Direction Implicit (ADI)-Parabolic Equation (ADI-PE) method offers greater numerical accuracy when solving complex boundary conditions. Therefore, the SSFT method is used to predict the propagation characteristics of electromagnetic interference in flat terrain. Furthermore, for complex terrain, the ADI-PE method is employed to calculate the propagation characteristics of electromagnetic interference.

[0093] The solution domain is divided into a large-scale complex geographical environment electromagnetic interference propagation region and an electromagnetic interference propagation region with obstacles.

[0094] Specifically, step S102 above includes, Figure 4 This is a schematic diagram of a method for constructing the electromagnetic signal propagation region transfer function based on the discrete Laplace transform according to an embodiment of the present invention.

[0095] To simplify the hybridization process and enable scene switching and modular simulation, the discrete Laplace transform is introduced into the multi-region hybridization method to extract the transfer function of electromagnetic interference propagation characteristics in each region. This transforms the prediction of electromagnetic interference propagation characteristics into the prediction of transfer function, thereby achieving the requirements of scene switching and modularization.

[0096] For example, suppose a sinusoidal modulated Gaussian pulse signal is used as the excitation source of the interference signal:

[0097]

[0098] In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c The center frequency is used. Then, the propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method, and the time-domain signal near the obstacle is solved, which is then used as the output signal y in the TDPE region. PE(t). Simultaneously, using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG (t). Then, based on the input and output signals of each region, the discrete Laplace transform is used to obtain the transfer function of different regions. Finally, the transfer functions are concatenated to obtain the transfer function H(z) of the entire electromagnetic interference propagation region.

[0099] After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.:

[0100] y(t)=x(t)*h(t) (2)

[0101] The transfer function of the TDPE region can be expressed as:

[0102]

[0103] In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively. Correspondingly, x(z) and y(z) are... PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation.

[0104] Similarly, Figure 4 In the figure, T1(z) and T2(z) are the system transfer functions of two multi-scale obstacles, respectively:

[0105]

[0106] The above method assumes that the distance between obstacles is far enough to ignore multiple scattering between them. If there is mutual coupling between obstacles, the DGTD method needs to be used to solve for the backscattering of the obstacles.

[0107] To facilitate obtaining the transfer function of electromagnetic interference propagation characteristics, such as Figure 5 As shown, this section uses the System Identification module in the Matlab simulation software. This module can quickly solve for the system transfer function coefficients based on the input and output signals.

[0108] Step S103, the method and apparatus for simulating electromagnetic signals in complex natural environments based on NI virtual instruments includes:

[0109] Specifically, the electromagnetic signal simulation device based on NI virtual instruments in complex natural environments consists of, for example: Figure 6As shown, the hardware system includes a radiation-based hardware-in-the-loop simulation. The interference signal output from the simulation is used to achieve a radiation-based electromagnetic effect hardware-in-the-loop simulation through NI Virtual Instruments, a power amplifier, and a transmitting antenna. The original electromagnetic signal is mixed with complex environmental characteristics using a LabVIEW program to obtain the output signal. The numerical simulation data is processed by NI Virtual Instruments and the output signal is then generated, thereby realizing the simulation of electromagnetic signals under complex natural environments.

[0110] The present invention provides an electromagnetic signal simulation method for complex natural environments, including a method for predicting the propagation characteristics of electromagnetic interference in complex multi-regional natural environments based on the time-domain discontinuous Galilean-parabolic equation; a method for constructing the electromagnetic signal propagation region transfer function based on the discrete Laplace transform; and a method and device for simulating electromagnetic signals in complex natural environments based on NI virtual instruments. The resulting electromagnetic effect simulation of complex environments can accurately simulate real-world electromagnetic environments. The simulation device simulates the electromagnetic signal interference experienced by equipment in complex natural environments, solving the problem of indoor simulations effectively replacing outdoor tests in environments with complex structural obstacles.

[0111] This embodiment provides a method for simulating electromagnetic signals in complex natural environments, which can be used in servers, such as desktop computers and tablets. Figure 2 This is a flowchart of an electromagnetic signal simulation method under complex natural environments according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0112] Step S201: A method for predicting the propagation characteristics of electromagnetic disturbances in complex multi-regional natural environments based on the time-domain discontinuous Galilean-parabolic equation.

[0113] Specifically, step S201 includes:

[0114] Step S2011: Decompose the solution domain into a large-area electromagnetic interference propagation region (TDPE region) and an obstacle forward scattering region (DGTD region).

[0115] Specifically, the Parabolic Equation (PE) method is derived by approximating Maxwell's wave equations. Compared to high-frequency approximation algorithms, the PE method fully considers the effects of electromagnetic wave refraction and diffraction, and also handles the refractive index term to account for environmental effects such as complex geographical and meteorological environments. However, for boundary problems such as rough surfaces, a large mesh can lead to certain errors in SSFT-PE, while the Alternating Direction Implicit (ADI)-Parabolic Equation (ADI-PE) method has a greater advantage in numerical accuracy when solving complex boundaries. Therefore, the solution region is first divided according to the complexity of the terrain.

[0116] Step S2012 involves calculating the propagation characteristics of electromagnetic interference signals under large-scale complex weather and terrain conditions using the Time-Domain Parabolic Equation (TDPE) method. In such regions, the SSFT method is then used to predict the propagation characteristics of electromagnetic interference in flat terrain.

[0117] In an optional implementation, step S2012 includes:

[0118] Step a1: Taking the large-area electromagnetic disturbance propagation region as the first solution region, and using scalar ψ to represent any field component of E or H, it satisfies the scalar Helmholtz equation:

[0119]

[0120] Step a2, assuming the electromagnetic wave propagates along the x-axis, define the wave function along the positive x-axis as:

[0121]

[0122] Substituting equation (6) into equation (5), we get:

[0123]

[0124] in Break the above expression into For the formula Expressed using the Feit-Fleck approximation method as The three-dimensional forward parabolic equation can be obtained as follows:

[0125]

[0126] Equation 7 is a first-order partial differential equation in x. Let the initial value of u(x,y,z) be u(x0,y,z). Then, solving Equation 8 yields:

[0127]

[0128] Separating the refractive index term and the constant term from Equation 9, we obtain:

[0129]

[0130] Define the two-dimensional Fourier transform and inverse Fourier transform in the YOZ plane as follows:

[0131]

[0132] After sorting, we can obtain:

[0133]

[0134] Step a3, assuming the atmosphere is a uniform medium, after simultaneously performing a two-dimensional Fourier transform and inverse Fourier transform on both sides of Equation 10, the solution formula for the three-dimensional parabolic equation using the SSFT method can be obtained as follows:

[0135]

[0136] Step S2013: The time-domain discontinuous Galois-Kinshasa (DGTD) method is used to calculate the time-domain scattering field of electromagnetic waves propagating into a region with complex structural obstacles. For complex boundaries, the ADI-PE method, which has higher solution accuracy, is used to calculate the complex boundary region.

[0137] In one optional implementation, step S2013 includes:

[0138] Step b1, Figure 7 This is a schematic diagram of the spatial stepping of the implicit solution with alternating directions.

[0139] x i y j z k Corresponding to the mesh nodes in the three dimensions, and:

[0140] x i =iΔx, i = 0, 1, ..., N x

[0141] y j =jΔy, j=0,1……,N y

[0142] z k =kΔz, k = 0, 1, ..., N z

[0143] Step b2, let ξ i Point x i-1 and x i The middle position between:

[0144]

[0145] According to the definition of central difference, the first-order partial derivative in the x-direction can be derived as follows:

[0146]

[0147] In the formula Represents u(x) i ,y j ,z k ).

[0148] Meanwhile, using the second-order partial derivatives of the central difference approximation equation, we have the following form:

[0149]

[0150] Take ξ i The field value at the distance is the distance between two whole grid points x. i-1 and x i The average value of the previous game, that is:

[0151]

[0152] In a 3D Cartesian coordinate system, the standard PE is:

[0153]

[0154] Position (ξ) i ,y j ,z k After difference calculus, substituting equations 15, 16, and 17 into equation 18 and rearranging, we obtain:

[0155]

[0156] Equation 19 can be rearranged as follows:

[0157] (1-r y δ y -r z δ z )u i =(1+r) y δ y +r z δ z )u i-1 (20)

[0158] in:

[0159]

[0160] Equation 20 is further transformed into:

[0161] (1-ry δ y -r z δ z +r y r z δ y δ z )u i =(1+r) y δ y +r z δ z +r y r z δ y δ z )u i-1 r y r z δ y δ z (u i -u i-1 )+O(ΔzΔx 2 )+O(ΔyΔx 2 )+O(Δx 3 ) (twenty four)

[0162] The O(*) term represents the nth-order error. The error term can be ignored. Furthermore, for ease of subsequent programming, the two steps in Equation 24 are separated onto both sides of the equals sign, resulting in:

[0163] (1-r y δ y (1-r) z δ z )u i =(1+r) y δ y (1+r) z δ z )u i-1 (25)

[0164] Step b3, for the ADI method, adds an intermediate step surface between the two surfaces. Its main function is to facilitate the mathematical solution; it has no specific physical meaning. For example... Figure 7 As shown, the field assumption on the step surface i-1 / 2 is as follows:

[0165] Equation 25 can then be decomposed into two equations:

[0166]

[0167] Substituting equation 26 into equation 25 and rearranging, we get:

[0168]

[0169] Equation 27 is the specific expression for the implicit solution method with alternating directions.

[0170] Step S202: Method for constructing the electromagnetic signal propagation region transfer function based on discrete Laplace transform.

[0171] Specifically, step S202 includes:

[0172] Step S2021: Calculate the propagation process of electromagnetic waves in complex weather and terrain environments using the TDPE method, solve for the time-domain signal near the obstacle, and use this as the output signal of the TDPE region.

[0173] In one optional implementation, step S2021 includes:

[0174] Specifically, let's assume that a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal:

[0175]

[0176] In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c The center frequency is used. Then, the propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method, and the time-domain signal near the obstacle is solved, which is then used as the output signal y in the TDPE region. PE (t).

[0177] Step S2022: Calculate the forward time-domain scattering field of each obstacle using the DGTD method.

[0178] In one optional implementation, step S2022 includes:

[0179] Specifically, x(t) is used as the excitation source, and the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG (t)

[0180] Step S2023: Based on the input and output signals of each region, the transfer function of different regions is obtained by using the discrete Laplace transform.

[0181] Step S2024: Cascade the transfer functions to obtain the transfer function of the entire electromagnetic interference propagation region.

[0182] In one optional implementation, step S2024 includes:

[0183] Specifically, the signal at the observation point after the electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene can be considered as the convolution of the initial signal and the transfer function, i.e.:

[0184] y(t)=x(t)*h(t) (29) The transfer function of the TDPE region can be expressed as:

[0185]

[0186] In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively. Correspondingly, x(z) and y(z) are... PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation.

[0187] Similarly, Figure 4 In the figure, T1(z) and T2(z) are the system transfer functions of two multi-scale obstacles, respectively:

[0188]

[0189] The above method assumes that the distance between obstacles is far enough to ignore multiple scattering between them. If there is mutual coupling between obstacles, the DGTD method needs to be used to solve for the backscattering of the obstacles.

[0190] Step S203: Method and apparatus for simulating electromagnetic signals in complex natural environments based on NI virtual instruments. For details, please refer to [link to details]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0191] This embodiment provides a method for calculating the propagation process of electromagnetic waves in complex weather and terrain environments using the TDPE method, and solves for the time-domain signal near obstacles, which is then used as the output signal of the TDPE region. The forward time-domain scattering field of each obstacle is calculated using the DGTD method. Based on the input and output signals of each region, the transfer function of different regions is obtained using the Discrete Laplace Transform. The transfer functions are then cascaded to obtain the transfer function of the entire electromagnetic disturbance propagation region. This provides a foundation for subsequent simulation of electromagnetic signals in complex natural environments.

[0192] This embodiment provides a method for simulating electromagnetic signals in complex natural environments, which can be used in servers, such as desktop computers and tablets. Figure 3 This is a flowchart of an electromagnetic signal simulation method under complex natural environments according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0193] Step S301: Use the LabVIEW program to mix the original electromagnetic signal with the complex environmental features to obtain the output signal.

[0194] Specifically, step S301 includes:

[0195] Step S3011: Read the electromagnetic environment data obtained from the measurement at the device end, and reconstruct the waveform data file.

[0196] Step S3012: Mix the original environmental data from the device with a transfer function representing the electromagnetic characteristics of the complex environment to obtain the electromagnetic signal from the device under the complex natural environment.

[0197] Step S302: The NI virtual instrument processes the numerical simulation data and outputs a signal. For details, please refer to [link to relevant documentation]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0198] This embodiment provides a method for simulating electromagnetic signals in complex natural environments. It uses a LabVIEW program to mix the original electromagnetic signal with complex environmental characteristics to obtain the output signal; then, NI virtual instruments process the numerical simulation data and output the signal. This achieves electromagnetic signal simulation in complex natural environments.

[0199] This embodiment also provides an electromagnetic environment effect simulation device under different environments. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0200] The structure of an electromagnetic signal simulation device for complex multi-region natural environments provided in this embodiment of the invention is as follows: Figure 8 As shown, it includes: a first computing module, a second computing module, and a third computing module;

[0201] The first calculation module acquires the topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments. Based on these characteristics, it uses the time-domain discontinuous Galerkin-parabolic DGTD method and the parabolic equation PE method to perform spatial discretization and numerical calculations, thereby acquiring electromagnetic disturbance propagation characteristic data for each region.

[0202] The second calculation module obtains the transfer function of different regions based on the electromagnetic interference propagation characteristic data of each region, the input electromagnetic signal and the output electromagnetic signal, and cascades the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region.

[0203] The third calculation module uses a LabVIEW program to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region based on the transfer function of the entire electromagnetic interference propagation region to obtain an output signal. The output signal is then simulated using NI virtual instruments and a radiation-type hardware-in-the-loop simulation device to obtain the simulated electromagnetic signals of the complex multi-regional natural environment.

[0204] In some optional implementations, the first calculation module is specifically used to acquire topographic, geomorphic, and meteorological condition characteristic parameters of complex multi-regional natural environments, and to perform spatial discretization and numerical calculation using the DGTD method and PE method based on the acquired characteristic parameters.

[0205] For flat terrain, the split-step Fourier transform (SSFT-PE) method is used to calculate the propagation process of electromagnetic waves and predict the propagation characteristics of electromagnetic disturbances in flat terrain.

[0206] For complex terrain and rough surfaces, the alternating direction implicit ADI-PE method is used to calculate the propagation characteristics of electromagnetic disturbances;

[0207] Calculate the time-domain signal near the obstacle as the output signal of the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacle.

[0208] The system outputs electromagnetic interference propagation characteristic data for each region. This data includes the frequency, intensity, waveform, propagation path, and phase information of the interference signal, as well as the time-domain signal near the obstacle. In some optional embodiments, the second calculation module is specifically used to obtain the transfer function of different regions using the discrete Laplace transform based on the electromagnetic interference propagation characteristic data, the input electromagnetic signal, and the output electromagnetic signal. The transfer functions of each region are then cascaded to obtain the transfer function of the entire electromagnetic interference propagation region, including:

[0209] Assuming a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal:

[0210]

[0211] In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c Center frequency

[0212] The propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method. The time-domain signal near the obstacle is then obtained and used as the output signal y in the TDPE region. PE Using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DGBased on the input and output signals of each region, the transfer function of each region is obtained by using the discrete Laplace transform. The transfer functions of different regions are cascaded to obtain the transfer function H(z) of the entire electromagnetic interference propagation region.

[0213] After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.:

[0214] y(t)=x(t)*h(t) (2)

[0215] The transfer function of the TDPE region is expressed as:

[0216]

[0217] In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively, x(z) and y(z). PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation.

[0218] Assuming the distance between the obstacles is large enough to ignore multiple scattering between them, T1(z) and T2(z) are the system transfer functions of the two multi-scale obstacles, respectively:

[0219]

[0220] T DG (z) is the transfer function of the DGTD region, x(z) and y DG (z) represent the input and output discrete-time signals x(k) and y(k) of the DGTD region, respectively. DG (k) The result after Z-transformation.

[0221] If there is mutual coupling between obstacles, the DGTD method can be used to solve for the backscattering of the obstacles.

[0222] In some optional implementations, the third calculation module is specifically used to use a LabVIEW program to mix the original electromagnetic signal of the entire electromagnetic interference propagation region with the characteristic parameters of the complex natural environment based on the transfer function of the entire electromagnetic interference propagation region, to obtain an output signal, and to perform simulation data processing on the output signal through NI virtual instruments to output a simulated electromagnetic signal.

[0223] The electromagnetic signals simulated by the radiation are processed by the power amplifier and the transmitting antenna to achieve radiation electromagnetic effect simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

[0224] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0225] In this embodiment, the electromagnetic signal simulation device under complex natural environment is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0226] This invention also provides a computer device having the above-described features. Figure 8 The device shown is an electromagnetic signal simulation apparatus for a complex, multi-regional natural environment. Please refer to [link / reference]. Figure 9 , Figure 9 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 9 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 9 Take a processor 10 as an example.

[0227] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0228] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0229] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0230] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0231] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means.

[0232] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0233] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0234] In summary, the electromagnetic signal simulation in complex natural environments established by this invention can accurately simulate the real electromagnetic environment in the field, solving the problem of indoor simulation equivalently replacing field tests in environments with complex structural obstacles.

[0235] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0236] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0237] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0238] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for simulating electromagnetic signals in complex multi-regional natural environments, characterized in that, include: The topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments are obtained. Based on these characteristics, the time-domain discontinuous Galilean-parabolic DGTD method and the parabolic equation PE method are used for spatial discretization and numerical calculation to obtain electromagnetic disturbance propagation characteristics data for each region. Based on the electromagnetic interference propagation characteristics data of each region, the input electromagnetic signal and the output electromagnetic signal, the transfer function of different regions is obtained by using the discrete Laplace transform. The transfer functions of each region are cascaded to obtain the transfer function of the entire electromagnetic interference propagation region. Based on the transfer function of the entire electromagnetic interference propagation area, the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation area are mixed using the LABVIEW program to obtain the output signal. The output signal is then simulated using the virtual instrument NI and a radiation-type hardware-in-the-loop simulation device to obtain the simulated electromagnetic signals of the complex multi-regional natural environment. The process involves acquiring topographic, geomorphological, and meteorological characteristic parameters of complex, multi-regional natural environments, and then using the DGTD and PE methods to perform spatial discretization and numerical calculations based on these parameters to obtain electromagnetic interference propagation characteristic data for each region. This includes: The topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments are obtained, and spatial discretization and numerical calculation are performed using the DGTD and PE methods based on the obtained characteristics. For flat terrain, the split-step Fourier transform (SSFT-PE) method is used to calculate the propagation process of electromagnetic waves and predict the propagation characteristics of electromagnetic disturbances in flat terrain. For complex terrain and rough surfaces, the alternating direction implicit ADI-PE method is used to calculate the propagation characteristics of electromagnetic disturbances; Calculate the time-domain signal near the obstacle as the output signal of the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacle. Output electromagnetic interference propagation characteristic data for each region. The electromagnetic interference propagation characteristic data includes the frequency, intensity, waveform, propagation path and phase information of the interference signal, as well as the time domain signal near the obstacle.

2. The method according to claim 1, characterized in that, The method described above, based on electromagnetic interference propagation characteristic data of each region, input electromagnetic signals, and output electromagnetic signals, uses discrete Laplace transform to obtain the transfer functions of different regions, and then cascades the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region. Assuming a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal: In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c Center frequency The propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method. The time-domain signal near the obstacle is then obtained and used as the output signal y in the TDPE region. PE Using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG Based on the input and output signals of each region, the transfer function of each region is obtained by using the discrete Laplace transform. The transfer functions of different regions are cascaded to obtain the transfer function H(z) of the entire electromagnetic interference propagation region. After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.: y(t)=x(t)*h(t) (2) The transfer function of the TDPE region is expressed as: In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively, x(z) and y(z). PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation; Assuming the distance between the obstacles is large enough to ignore multiple scattering between them, T1(z) and T2(z) are the system transfer functions of the two multi-scale obstacles, respectively: T DG (z) is the transfer function of the DGTD region, x(z) and y DG (z) represent the input and output discrete-time signals x(k) and y(k) of the DGTD region, respectively. DG (k) The result after Z-transformation; If there is mutual coupling between obstacles, the DGTD method can be used to solve for the backscattering of the obstacles.

3. The method according to claim 2, characterized in that, The process involves using LabVIEW to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region based on the transfer function of the entire region, obtaining an output signal, and then using NI virtual instruments and a radiation-based hardware-in-the-loop simulation device to simulate and process the output signal to obtain the simulated electromagnetic signals of the complex multi-regional natural environment. This includes: Based on the transfer function of the entire electromagnetic interference propagation area, the original electromagnetic signal of the entire electromagnetic interference propagation area and the characteristic parameters of the complex natural environment are mixed using the LABVIEW program to obtain the output signal. The output signal is then processed by the NI virtual instrument to output the simulated electromagnetic signal. The electromagnetic signals simulated by the radiation are processed by the power amplifier and the transmitting antenna to achieve radiation electromagnetic effect simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

4. A simulation device for electromagnetic signals in complex multi-regional natural environments, characterized in that, include: The first calculation module, the second calculation module, and the third calculation module; The first calculation module acquires the topographic, geomorphological, and meteorological characteristics of complex multi-regional natural environments. Based on these characteristics, it uses the time-domain discontinuous Galerkin-parabolic DGTD method and the parabolic equation PE method to perform spatial discretization and numerical calculations, thereby acquiring electromagnetic disturbance propagation characteristic data for each region. The second calculation module obtains the transfer function of different regions based on the electromagnetic interference propagation characteristic data of each region, the input electromagnetic signal and the output electromagnetic signal, and cascades the transfer functions of each region to obtain the transfer function of the entire electromagnetic interference propagation region. The third calculation module uses the LabVIEW program to mix the original electromagnetic signals and characteristic parameters of the entire electromagnetic interference propagation region according to the transfer function of the entire electromagnetic interference propagation region to obtain the output signal. The output signal is then simulated using NI virtual instruments and a radiation-type hardware-in-the-loop simulation device to obtain the simulated electromagnetic signals of the complex multi-regional natural environment. The first calculation module is specifically used to obtain the topographic, geomorphological and meteorological condition characteristic parameters of complex multi-regional natural environments, and to perform spatial discretization and numerical calculation using the DGTD method and PE method based on the obtained characteristic parameters. For flat terrain, the split-step Fourier transform (SSFT-PE) method is used to calculate the propagation process of electromagnetic waves and predict the propagation characteristics of electromagnetic disturbances in flat terrain. For complex terrain and rough surfaces, the alternating direction implicit ADI-PE method is used to calculate the propagation characteristics of electromagnetic disturbances; Calculate the time-domain signal near the obstacle as the output signal of the TDPE region. If there is mutual coupling between the obstacles, use the DGTD method to solve for the backscattering of the obstacle. Output electromagnetic interference propagation characteristic data for each region. The electromagnetic interference propagation characteristic data includes the frequency, intensity, waveform, propagation path and phase information of the interference signal, as well as the time domain signal near the obstacle.

5. The apparatus according to claim 4, characterized in that: The second calculation module is specifically used to obtain the transfer function of different regions based on the electromagnetic interference propagation characteristic data of each region, the input electromagnetic signal, and the output electromagnetic signal, using the discrete Laplace transform. The transfer functions of each region are then cascaded to obtain the transfer function of the entire electromagnetic interference propagation region, including: Assuming a sinusoidal modulated Gaussian pulse signal is used as the excitation source for the interference signal: In the formula, A is the signal amplitude, T is the pulse period, t0 is the time delay, and f c Center frequency The propagation process of electromagnetic waves in complex weather and terrain environments is calculated using the TDPE method. The time-domain signal near the obstacle is then obtained and used as the output signal y in the TDPE region. PE Using x(t) as the excitation source, the forward time-domain scattered field y of each obstacle is calculated using the DGTD method. DG Based on the input and output signals of each region, the transfer function of each region is obtained by using the discrete Laplace transform. The transfer functions of different regions are cascaded to obtain the transfer function H(z) of the entire electromagnetic interference propagation region. After an electromagnetic interference signal passes through an obstacle-filled environment in a large-scale scene, the signal at the observation point can be considered as the convolution of the initial signal and the transfer function, i.e.: y(t)=x(t)*h(t) (2) The transfer function of the TDPE region is expressed as: In the formula, Z(*) represents the Z-transform, and x(k) and y PE (k) represent the input and output discrete-time signals of the TDPE region, respectively, x(z) and y(z). PE (z) represent x(k) and y respectively. PE (k) The result after Z-transformation; Assuming the distance between the obstacles is large enough to ignore multiple scattering between them, T1(z) and T2(z) are the system transfer functions of the two multi-scale obstacles, respectively: T DG (z) is the transfer function of the DGTD region, x(z) and y DG (z) represent the input and output discrete-time signals x(k) and y(k) of the DGTD region, respectively. DG (k) The result after Z-transformation; If there is mutual coupling between obstacles, the DGTD method can be used to solve for the backscattering of the obstacles.

6. The apparatus according to claim 5, characterized in that: The third calculation module is specifically used to use a LabVIEW program to mix the original electromagnetic signal of the entire electromagnetic interference propagation area with the characteristic parameters of the complex natural environment based on the transfer function of the entire electromagnetic interference propagation area, to obtain an output signal, and to perform simulated data processing on the output signal through NI virtual instruments to output a simulated electromagnetic signal. The electromagnetic signals simulated by the radiation are processed by the power amplifier and the transmitting antenna to achieve radiation electromagnetic effect simulation, thereby obtaining the simulated electromagnetic signals of the complex multi-regional natural environment.

7. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the electromagnetic signal simulation method for complex multi-regional natural environments as described in any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the electromagnetic signal simulation method for complex multi-regional natural environments as described in any one of claims 1 to 3.

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