A far-field electromagnetic pulse waveform simulation method and system

Abstract

The present invention provides a far-field electromagnetic pulse waveform simulation method and system. The method introduces an international reference geomagnetic model, an international reference ionosphere model and an international reference atmosphere model when calculating the waveguide parameters of a single-frequency signal along a path segment in an LWPC model. The obtained geomagnetic parameters, ionospheric electron density and electron collision frequency include the influence of time and space, solar disturbances and geomagnetic changes, and are used for simulating far-field electromagnetic pulse waveforms, thereby improving the simulation accuracy of far-field electromagnetic pulse waveforms.

Description

Technical Field

[0001] The present invention belongs to the technical field of electromagnetic pulse waveform simulation, and in particular relates to a far-field electromagnetic pulse waveform simulation method and system. Background Art

[0002] For the simulation of far-field very low frequency / low frequency electromagnetic pulse waveform, the frequency range is generally 3kHz to 60kHz. Because its main frequency is generally in the very low frequency band, it can also be called far-field very low frequency electromagnetic pulse waveform simulation.

[0003] For very low frequency electromagnetic pulse simulation, the commonly used method is the finite-difference time-domain (FDTD) method. However, when dealing with long wavelength and large spatial range propagation problems, the FDTD method inevitably has serious problems such as complex boundary conditions, high computing resource requirements, and long calculation time. As a result, the method has poor stability and low efficiency, making it difficult to implement in engineering.

[0004] In addition, the LWPC model is an engineering model used to calculate the propagation field strength and phase of single-frequency very low frequency / low frequency signals. The LWPC model can be used to realize the engineering simulation calculation of far-field very low frequency / low frequency electromagnetic pulse waveforms. However, the built-in ionosphere model of the LWPC model only considers the transition from day to night and the transition from the geomagnetic latitude area to the polar cap area at night. The disadvantage of this model is that the values ​​during the day and night are constants, which cannot reflect the changes of the ionosphere over time and space, thus affecting the accuracy of waveform simulation to a certain extent. Secondly, the built-in geomagnetic model of the LWPC model does not consider the impact of the annual changes in the earth's crust.

[0005] The present invention proposes to use the International Reference Ionosphere Model IRI, the International Reference Atmosphere Model MSIS and the International Geomagnetic Field Model IGRF to generate the ionospheric parameters and geomagnetic parameters required by the LWPC model, and then use frequency division calculation and multi-frequency synthesis technology to obtain the far-field electromagnetic pulse waveform to improve the waveform simulation accuracy. Electromagnetic pulses can have a serious impact on electronic equipment, power facilities and communication infrastructure. Obtaining the far-field receiving waveform of the electromagnetic pulse source propagating to any location through simulation technology helps people understand the propagation characteristics of electromagnetic pulses, which is of great significance for analyzing and protecting against electromagnetic pulse hazards. Summary of the invention

[0006] Based on this, an embodiment of the present invention provides a far-field electromagnetic pulse waveform simulation method and system, aiming to improve the simulation accuracy of the far-field electromagnetic pulse waveform.

[0007] A first aspect of an embodiment of the present invention provides a far-field electromagnetic pulse waveform simulation method, the method comprising:

[0008] Provide a source waveform and initialize parameters. Specifically, the step of initializing parameters includes setting event occurrence time, source area coordinates, path segmentation step, receiving coordinates, and time sampling resolution;

[0009] The initialized parameters are used as the input of the LWPC model, and the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point are calculated based on the IGRF model, the IRI model and the MSIS model, and then the corresponding parameters in the LWPC model are replaced;

[0010] Calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, and replacing the electron collision frequency in the LWPC model;

[0011] Performing Fourier transformation on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform;

[0012] Based on the optimized LWPC model, the amplitude and phase changes of each frequency point along the propagation path are calculated, and the amplitude spectrum and phase spectrum of the source waveform are superimposed with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the signal at the far-field receiving point.

[0013] The amplitude spectrum and phase spectrum of the far-field receiving point signal are inversely transformed by Fourier transform to obtain the far-field time-domain simulation waveform.

[0014] Furthermore, the steps of using the initialized parameters as inputs of the LWPC model, and respectively calculating the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point based on the IGRF model, the IRI model and the MSIS model, and then replacing the corresponding parameters in the LWPC model include:

[0015] The initialized parameters are used as inputs of the LWPC model, and the geomagnetic parameters of each segmentation point are calculated based on the IGRF model, and then the geomagnetic parameters in the LWPC model are replaced, wherein the geomagnetic parameters include geomagnetic inclination, geomagnetic declination and geomagnetic component intensity, wherein the segmentation point is determined according to the source area coordinates, the receiving coordinates and the path segmentation step length;

[0016] Based on the IRI model, the electronic parameters within the ionospheric height range of each segmented point are calculated according to the event occurrence time, the longitude and latitude coordinates of the segmented points, the ionospheric profile height range and the height step, and the electronic parameters in the LWPC model are replaced, wherein the electronic parameters include electron density, electron temperature and ion density, and the ions include nitric oxide positive ions, oxygen positive ions and oxygen positive ions;

[0017] Based on the MSIS model, the concentration of neutral particles within the ionospheric height range is calculated layer by layer according to the ionospheric profile height range, the height step, the event occurrence time, the longitude and latitude coordinates of the segmentation points, the global AP index, the global f107 index, the AP index mean at a preset time, and the f107 index mean at a preset time. The neutral particles include nitrogen, oxygen, oxygen atoms, and helium.

[0018] Furthermore, the source waveform is a standard double exponential pulse waveform or a near-zone measured waveform.

[0019] Furthermore, in the step of determining the segmentation point according to the source coordinates, the receiving coordinates and the path segmentation step length, the geographical great circle path distance is calculated according to the source coordinates and the receiving coordinates, and then the geographical great circle path distance is divided by the path segmentation step length to obtain the number of segments, wherein the longitude and latitude coordinates of the segmentation point of each segment are expressed as ( , )(i=1,2,...,N), N is the number of segments.

[0020] Furthermore, the ionospheric profile height range is 50km~150km.

[0021] Furthermore, the preset time is 3 months.

[0022] Furthermore, in the step of calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, the expression of the collision frequency between electrons and neutral particles is:

[0023]

[0024]

[0025]

[0026]

[0027] The expression for the collision frequency between electrons and ions is:

[0028]

[0029] The expression for the total electron collision frequency is:

[0030]

[0031] in, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and oxygen molecules, is the collision frequency between electrons and oxygen atoms, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and i-type ions, is the concentration of nitrogen molecules, is the concentration of oxygen molecules, is the oxygen atomic concentration, is the concentration of helium molecules, for The concentration of ions, is the electron temperature.

[0032] A second aspect of an embodiment of the present invention provides a far-field electromagnetic pulse waveform simulation system, which is used to implement the far-field electromagnetic pulse waveform simulation method provided in the first aspect, and the system includes:

[0033] An initialization module is used to provide a source waveform and initialize parameters. Specifically, the step of initializing parameters includes setting the event occurrence time, source area coordinates, path segmentation step, receiving coordinates, and time sampling resolution;

[0034] A replacement module is used to use the initialized parameters as the input of the LWPC model, and calculate the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point based on the IGRF model, the IRI model and the MSIS model, and then replace the corresponding parameters in the LWPC model;

[0035] A calculation module, used for calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, and replacing the electron collision frequency in the LWPC model;

[0036] A Fourier transform module, used for performing Fourier transform on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform;

[0037] A superposition module is used to calculate the amplitude and phase changes of each frequency point along the propagation path based on the optimized LWPC model, and to superimpose the amplitude spectrum and phase spectrum of the source waveform with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the signal at the far-field receiving point;

[0038] The inverse Fourier transform module is used to perform inverse Fourier transform on the amplitude spectrum and phase spectrum of the far-field receiving point signal to obtain a far-field time-domain simulation waveform.

[0039] A third aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the far-field electromagnetic pulse waveform simulation method provided in the first aspect.

[0040] A fourth aspect of an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the far-field electromagnetic pulse waveform simulation method provided in the first aspect is implemented.

[0041] A far-field electromagnetic pulse waveform simulation method and system provided in an embodiment of the present invention provides a source waveform and initializes parameters; uses the parameters as input of an LWPC model, and calculates geomagnetic parameters of each segment point based on an IGRF model, and then replaces the geomagnetic parameters in the LWPC model; calculates electronic parameters within the ionospheric height range of each segment point based on the IRI model and corresponding parameters, and replaces the electronic parameters in the LWPC model; calculates the neutral particle concentration within the ionospheric height range layer by layer based on the MSIS model and corresponding parameters; calculates the electron collision frequency of each ionosphere based on the electron temperature, ion density and neutral particle concentration, and replaces the electron collision frequency in the LWPC model; performs Fourier transformation on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform; calculates the amplitude and phase changes of each frequency point along the propagation path based on the optimized LWPC model, and superimposes the amplitude spectrum and the phase spectrum of the source waveform with the amplitude and the phase changes of the propagation path to obtain the amplitude spectrum and the phase spectrum of the far-field receiving point signal, and then performs inverse Fourier transformation to obtain a high-precision far-field time-domain simulation waveform. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flowchart of a far-field electromagnetic pulse waveform simulation method provided in Embodiment 1 of the present invention;

[0043] Figure 2 It is a schematic diagram of the near-field measured waveform;

[0044] Figure 3 A comparison chart showing the variation of the logarithm of electron density with height calculated using the LWPC built-in model and the far-field electromagnetic pulse waveform simulation method proposed in the present invention;

[0045] Figure 4 A comparison chart showing the change in the logarithm of the electron collision frequency with height calculated using the LWPC built-in model and the far-field electromagnetic pulse waveform simulation method proposed in the present invention;

[0046] Figure 5 A comparison diagram of the simulation results obtained by the far-field electromagnetic pulse waveform simulation method proposed in the present invention and the measured waveform;

[0047] Figure 6 A structural block diagram of a far-field electromagnetic pulse waveform simulation system provided in Embodiment 3 of the present invention;

[0048] Figure 7This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0049] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0050] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0052] Embodiment 1

[0053] According to an embodiment of the present invention, a method for simulating a far-field electromagnetic pulse waveform is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0054] In this embodiment 1, a method for simulating a far-field electromagnetic pulse waveform is provided, which can be used in electronic devices, such as computers. Figure 1 , Figure 1 A flowchart of a far-field electromagnetic pulse waveform simulation method provided in Embodiment 1 of the present invention is shown, which specifically includes steps S01 to S08.

[0055] Step S01, providing a source waveform and initializing parameters. Specifically, the step of initializing parameters includes setting event occurrence time, source area coordinates, path segmentation step length, receiving coordinates and time sampling resolution.

[0056] Specifically, set the event occurrence time (YYYY, MM, DD, hh, mm, ss), source area coordinates ( , ), event source intensity, path segment step length ( ), channel noise ( )、Receive coordinates( , ), sampling resolution ( ). To carry out the simulation of far-field electromagnetic pulse waveform, a source waveform is also required. The source waveform can use a standard double exponential pulse waveform or a near-field measured waveform instead.

[0057] Step S02, using the initialized parameters as the input of the LWPC model, and calculating the geomagnetic parameters of each segmentation point based on the IGRF model, and then replacing the geomagnetic parameters in the LWPC model, the geomagnetic parameters including geomagnetic inclination, geomagnetic declination and geomagnetic component intensity, wherein the segmentation point is determined according to the source area coordinates, the receiving coordinates and the path segmentation step.

[0058] Among them, LWPC (Long Wavelength Propagation Capability) is a FORTRAN program developed based on waveguide mode theory to simulate very low frequency electromagnetic wave propagation. The program can automatically plan the propagation path to simulate very low frequency wave propagation as long as the transmitter and receiver are determined. The overall work of LWPC is mainly divided into three processes: waveguide parameter segmentation (PRESEG), mode solution (MODEFINER), and mode conversion (FASTMC).

[0059] Specifically, firstly, the geographic great circle path distance is calculated according to the source area coordinates and the receiving coordinates, and then the geographic great circle path distance is divided by the path segmentation step length to obtain the number of segments, wherein the longitude and latitude coordinates of the segmentation points of each segment are expressed as ( , )(i=1,2,...,N), N is the number of segments.

[0060] Then determine the waveguide parameters of each segmentation point. When calculating the segmentation point parameters, the IGRF call submodule is embedded in the LWPC model, and the event time (YYYY, MM, DD, hh, mm, ss), the segmentation point longitude and latitude coordinates ( , )(i=1,N), altitude (h), calculate the geomagnetic inclination, declination and geomagnetic component intensity of each segment point in turn, and replace the geomagnetic parameters in the LWPC model.

[0061] It should be noted that the IGRF (International Geomagnetic Reference Field) model is a mathematical model of the Earth's main magnetic field and its long-term changes. It uses spherical harmonic analysis to represent the Earth's magnetic field as the sum of a series of spherical harmonic functions, and describes the distribution of the Earth's magnetic field in space and time by determining spherical harmonic coefficients. These coefficients are determined by global geomagnetic stations and satellite magnetic survey data.

[0062] Step S03, based on the IRI model, according to the time of occurrence of the event, the longitude and latitude coordinates of the segmentation points, the ionospheric profile height range and the height step, calculate the electronic parameters within the ionospheric height range of each segmentation point, and replace the electronic parameters in the LWPC model, wherein the electronic parameters include electron density, electron temperature and ion density, and the ions include nitric oxide positive ions, oxygen positive ions and oxygen positive ions.

[0063] Among them, the ionospheric profile height range is 50km~150km. It should be noted that the IRI (International Reference Ionosphere) model is a global ionospheric model used to describe the distribution and changes of electron density in the ionosphere. It is an empirical model that establishes the relationship between input and output variables based on statistical analysis of observational data.

[0064] Step S04, based on the MSIS model, according to the ionospheric profile height range, the height step, the event occurrence time, the longitude and latitude coordinates of the segmentation point, the global ap index, the global f107 index, the ap index mean at a preset time, and the f107 index mean at a preset time, the neutral particle concentration within the ionospheric height range is calculated layer by layer, and the neutral particles include nitrogen, oxygen, oxygen atoms, and helium.

[0065] Among them, the preset time is 3 months, that is, the 3-month average of the AP index and the 3-month average of the F107 index. It should be noted that the MSIS (Mass Spectrometer Incoherent Scatter, atmospheric density and ionosphere) model is a static and dynamic atmospheric chemistry model, as well as an atmospheric and ionosphere physical model. The relevant model is established by integrating multiple factors to reflect the changes and distribution of relevant parameters of the atmosphere and ionosphere.

[0066] Step S05, calculating the electron collision frequency of each ionosphere according to the electron temperature, the ion density and the neutral particle concentration, and replacing the electron collision frequency in the LWPC model.

[0067] In this embodiment, the expression of the collision frequency between electrons and neutral particles is:

[0068]

[0069]

[0070]

[0071]

[0072] The expression for the collision frequency between electrons and ions is:

[0073]

[0074] The expression for the total electron collision frequency is:

[0075]

[0076] in, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and oxygen molecules, is the collision frequency between electrons and oxygen atoms, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and i-type ions, is the concentration of nitrogen molecules, is the concentration of oxygen molecules, is the oxygen atomic concentration, is the concentration of helium molecules, for The concentration of ions, is the electron temperature.

[0077] Step S06, performing Fourier transform on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform.

[0078] Step S07, based on the optimized LWPC model, calculate the amplitude and phase changes of each frequency point along the propagation path, and superimpose the amplitude spectrum and phase spectrum of the source waveform with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the far-field receiving point signal.

[0079] Step S08, performing inverse Fourier transform on the amplitude spectrum and phase spectrum of the far-field receiving point signal to obtain a far-field time-domain simulation waveform.

[0080] In summary, the far-field electromagnetic pulse waveform simulation method in the above-mentioned embodiment of the present invention provides a source waveform and initializes parameters; uses the parameters as the input of the LWPC model, and calculates the geomagnetic parameters of each segment point based on the IGRF model, and then replaces the geomagnetic parameters in the LWPC model; based on the IRI model, calculates the electronic parameters within the ionospheric height range of each segment point according to the corresponding parameters, and replaces the electronic parameters in the LWPC model; based on the MSIS model, calculates the neutral particle concentration within the ionospheric height range layer by layer according to the corresponding parameters; calculates the electron collision frequency of each ionosphere according to the electron temperature, ion density and neutral particle concentration, and replaces the electron collision frequency in the LWPC model; Fourier transforms the source waveform to obtain the amplitude spectrum and phase spectrum of the source waveform; based on the optimized LWPC model, calculates the amplitude and phase change of each frequency point along the propagation path, and superimposes the amplitude spectrum and phase spectrum of the source waveform with the amplitude and phase change of the propagation path to obtain the amplitude spectrum and phase spectrum of the far-field receiving point signal, and then performs inverse Fourier transform to obtain a high-precision far-field time domain simulation waveform.

[0081] Embodiment 2

[0082] In order to verify the far-field electromagnetic pulse waveform simulation method in the first embodiment of the present invention, a specific far-field waveform simulation experimental example is given in the second embodiment of the present invention. Specifically, the source area coordinates are Nevada (37.1347°N, 116.0408°W), the receiving point coordinates are Rapid (44.1131°N, 103.3489°W), and the propagation distance is 1320km. The event occurred at 13:00:00 on October 7, 1957, world time. The segment step size is 20km, the duration is 1ms, and the time sampling resolution is 2MHz. The input source waveform is a publicly measured near-field waveform, such as Figure 2 As shown, the waveform is the time domain waveform and frequency domain waveform measured in the near field;

[0083] Calculate the waveguide parameters of the segment points along the propagation path, input 13:00:00 on October 7, 1957, the longitude and latitude of the segment points, and set the altitude to 80km in the IGRF call submodule. The geomagnetic declination, geomagnetic inclination and geomagnetic intensity output by IGRF replace the geomagnetic parameters in the LWPC model;

[0084] Using the source time, segmentation point longitude and latitude, altitude range (50~150km), and altitude step (1km) as input parameters, the IRI model is called to calculate the electron density within the range of 50~150km of the segmentation point along the propagation path. , ion density )、n( 、n( ), electron temperature ;

[0085] First, download and calculate the global f107 value, three-month average f107 value, ap value, three-month average ap value and other parameter values ​​at the time of the event. Take these index parameter values ​​and the source time, location, altitude range (50km~150km), and altitude step (1km) as input parameters, and call the MSIS model to calculate the density of four types of neutral particles in the altitude range of 50~150km. ;

[0086] Electron density based on IRI and MSIS model output ), ion density )、n( 、n( ), neutral particle density , electron temperature The collision frequency in the range of 50km~150km above the segmentation point is calculated by using the same parameters;

[0087] Figure 3 This is a comparison chart of the electron density calculated by the LWPC built-in model and the far-field electromagnetic pulse waveform simulation method proposed in this invention, taking the logarithm of the electron density as a function of height. Figure 4 This is a comparison diagram of the logarithm of the electron collision frequency calculated using the LWPC built-in model and the far-field electromagnetic pulse waveform simulation method proposed in the present invention. The actual model represents the original model, and the dotted line represents the optimized model, that is, the result calculated by the far-field electromagnetic pulse waveform simulation method proposed in the present invention. It can be found that the electron density and the logarithm of the electron collision frequency calculated by the far-field electromagnetic pulse waveform simulation method proposed in the embodiment of the present invention vary nonlinearly with height, which is more in line with the actual ionospheric environment.

[0088] The frequency resolution is set to 1kHz, the frequency range is 3kHz~60kHz, and the optimized propagation model is called in parallel by multiple threads. The amplitude and phase of signals at different frequency points attenuating along the path are calculated by frequency division, and a channel attenuation model is constructed. Combined with the LWPC electromagnetic pulse waveform simulation technology, far-field electromagnetic pulse waveform simulation is performed. Figure 5 A comparison between the simulation results of the far-field electromagnetic pulse waveform simulation method proposed in the present invention and the measured waveform is given. The correlation coefficient between the simulation waveform obtained by directly using the traditional LWPC model and the measured waveform is about 0.85, while the correlation coefficient between the simulation waveform obtained by the far-field electromagnetic pulse waveform simulation method proposed in the present invention and the measured waveform is 0.91, which improves the simulation accuracy.

[0089] Embodiment 3

[0090] See also Figure 6 , Figure 6This is a structural block diagram of a far-field electromagnetic pulse waveform simulation system provided by Embodiment 3 of the present invention. The far-field electromagnetic pulse waveform simulation system 200 is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0091] Specifically, the far-field electromagnetic pulse waveform simulation system 200 includes: an initialization module 21, a replacement module 22, a calculation module 23, a Fourier transform module 24, a superposition module 25 and an inverse Fourier transform module 26, wherein:

[0092] Initialization module 21, used to provide source waveform and initialize parameters, specifically, the step of initializing parameters includes setting event occurrence time, source area coordinates, event source intensity, path segmentation step, channel noise, receiving coordinates and time sampling resolution, wherein the source waveform is a standard double exponential pulse waveform or a near-area measured waveform;

[0093] A replacement module 22 is used to use the initialized parameters as input of the LWPC model, and calculate the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point based on the IGRF model, the IRI model and the MSIS model, and then replace the corresponding parameters in the LWPC model;

[0094] The calculation module 23 is used to calculate the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, and replace the electron collision frequency in the LWPC model. The expression of the collision frequency between electrons and neutral particles is:

[0095]

[0096]

[0097]

[0098]

[0099] The expression for the collision frequency between electrons and ions is:

[0100]

[0101] The expression for the total electron collision frequency is:

[0102]

[0103] in, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and oxygen molecules, is the collision frequency between electrons and oxygen atoms, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and i-type ions, is the concentration of nitrogen molecules, is the concentration of oxygen molecules, is the oxygen atomic concentration, is the concentration of helium molecules, for The concentration of ions, is the electron temperature;

[0104] A Fourier transform module 24 is used to perform Fourier transform on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform;

[0105] The superposition module 25 is used to calculate the amplitude and phase changes of each frequency point along the propagation path based on the optimized LWPC model, and superimpose the amplitude spectrum and phase spectrum of the source waveform with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the far-field receiving point signal;

[0106] The inverse Fourier transform module 26 is used to perform inverse Fourier transform on the amplitude spectrum and phase spectrum of the far-field receiving point signal to obtain a far-field time-domain simulation waveform.

[0107] Furthermore, in some other embodiments of the present invention, the replacement module 22 includes:

[0108] The first replacement unit is used to use the initialized parameters as the input of the LWPC model, and calculate the geomagnetic parameters of each segmentation point based on the IGRF model, and then replace the geomagnetic parameters in the LWPC model, wherein the geomagnetic parameters include geomagnetic inclination, geomagnetic declination and geomagnetic component intensity, wherein the segmentation point is determined according to the source area coordinates, the receiving coordinates and the path segmentation step length, and the geographic great circle path distance is calculated according to the source area coordinates and the receiving coordinates, and then the geographic great circle path distance is divided by the path segmentation step length to obtain the number of segments, wherein the longitude and latitude coordinates of the segmentation point of each segment are expressed as ( , )(i=1,2,...,N), N is the number of segments;

[0109] A second replacement unit is used to calculate the electronic parameters within the ionospheric height range of each segmented point based on the IRI model according to the event occurrence time, the longitude and latitude coordinates of the segmented point, the ionospheric profile height range and the height step, and replace the electronic parameters in the LWPC model, wherein the electronic parameters include electron density, electron temperature and ion density, and the ions include nitric oxide positive ions, oxygen positive ions and oxygen positive ions, and the ionospheric profile height range is 50km~150km;

[0110] The third replacement unit is used to calculate the concentration of neutral particles within the ionospheric height range layer by layer based on the MSIS model according to the ionospheric profile height range, the height step, the event occurrence time, the longitude and latitude coordinates of the segmentation point, the global AP index, the global f107 index, the AP index mean at a preset time, and the f107 index mean at a preset time, wherein the neutral particles include nitrogen, oxygen, oxygen atoms and helium, and the preset time is 3 months.

[0111] Embodiment 4

[0112] Another aspect of the present invention provides an electronic device, see Figure 7 , shown is an electronic device in Embodiment 4 of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor, wherein the processor 10 implements the far-field electromagnetic pulse waveform simulation method as described above when executing the computer program 30.

[0113] In some embodiments, the processor 10 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 20, such as executing access restriction programs.

[0114] The memory 20 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 20 may be an internal storage unit of an electronic device, such as a hard disk of the electronic device. In other embodiments, the memory 20 may also be an external storage device of an electronic device, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Further, the memory 20 may also include both an internal storage unit and an external storage device of the electronic device. The memory 20 may be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or is to be output.

[0115] It should be pointed out that Figure 7 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than those shown in the figure, or combine certain components, or arrange the components differently.

[0116] The embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the far-field electromagnetic pulse waveform simulation method as described above is implemented.

[0117] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0118] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0119] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0120] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0121] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A method for simulating a far-field electromagnetic pulse waveform, characterized in that: The method comprises: Provide a source waveform and initialize parameters. Specifically, the step of initializing parameters includes setting event occurrence time, source area coordinates, path segmentation step, receiving coordinates, and time sampling resolution; The initialized parameters are used as the input of the LWPC model, and the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point are calculated based on the IGRF model, the IRI model and the MSIS model, and then the corresponding parameters in the LWPC model are replaced; Calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, and replacing the electron collision frequency in the LWPC model; Performing Fourier transformation on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform; Based on the optimized LWPC model, the amplitude and phase changes of each frequency point along the propagation path are calculated, and the amplitude spectrum and phase spectrum of the source waveform are superimposed with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the signal at the far-field receiving point. The amplitude spectrum and phase spectrum of the far-field receiving point signal are inversely transformed by Fourier transform to obtain the far-field time-domain simulation waveform.

2. The far-field electromagnetic pulse waveform simulation method according to claim 1, characterized in that: The steps of using the initialized parameters as the input of the LWPC model, and respectively calculating the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point based on the IGRF model, the IRI model and the MSIS model, and then replacing the corresponding parameters in the LWPC model include: The initialized parameters are used as inputs of the LWPC model, and the geomagnetic parameters of each segmentation point are calculated based on the IGRF model, and then the geomagnetic parameters in the LWPC model are replaced, wherein the geomagnetic parameters include geomagnetic inclination, geomagnetic declination and geomagnetic component intensity, wherein the segmentation point is determined according to the source area coordinates, the receiving coordinates and the path segmentation step length; Based on the IRI model, the electronic parameters within the ionospheric height range of each segmented point are calculated according to the event occurrence time, the longitude and latitude coordinates of the segmented points, the ionospheric profile height range and the height step, and the electronic parameters in the LWPC model are replaced, wherein the electronic parameters include electron density, electron temperature and ion density, and the ions include nitric oxide positive ions, oxygen positive ions and oxygen positive ions; Based on the MSIS model, the concentration of neutral particles within the ionospheric height range is calculated layer by layer according to the ionospheric profile height range, the height step, the event occurrence time, the longitude and latitude coordinates of the segmentation points, the global AP index, the global f107 index, the AP index mean at a preset time, and the f107 index mean at a preset time. The neutral particles include nitrogen, oxygen, oxygen atoms, and helium.

3. The far-field electromagnetic pulse waveform simulation method according to claim 2, characterized in that: The source waveform is a standard double exponential pulse waveform or a near-zone measured waveform.

4. The far-field electromagnetic pulse waveform simulation method according to claim 3 is characterized in that: In the step of determining the segmentation point according to the source coordinates, the receiving coordinates and the path segmentation step length, the geographic great circle path distance is calculated according to the source coordinates and the receiving coordinates, and then the geographic great circle path distance is divided by the path segmentation step length to obtain the number of segments, wherein the longitude and latitude coordinates of the segmentation point of each segment are expressed as ( , )(i=1,2,...,N), N is the number of segments.

5. The far-field electromagnetic pulse waveform simulation method according to claim 4, characterized in that: The ionospheric profile height range is 50km~150km.

6. The far-field electromagnetic pulse waveform simulation method according to claim 5, characterized in that: The preset time is 3 months.

7. The far-field electromagnetic pulse waveform simulation method according to claim 6, characterized in that: In the step of calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, the expression of the collision frequency between electrons and neutral particles is: The expression for the collision frequency between electrons and ions is: The expression for the total electron collision frequency is: in, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and oxygen molecules, is the collision frequency between electrons and oxygen atoms, is the collision frequency between electrons and nitrogen molecules, is the collision frequency between electrons and i-type ions, is the concentration of nitrogen molecules, is the concentration of oxygen molecules, is the oxygen atomic concentration, is the concentration of helium molecules, for The concentration of ions, is the electron temperature.

8. A far-field electromagnetic pulse waveform simulation system, characterized in that: Used to implement the far-field electromagnetic pulse waveform simulation method according to any one of claims 1 to 7, the system comprises: An initialization module is used to provide a source waveform and initialize parameters. Specifically, the step of initializing parameters includes setting the event occurrence time, source area coordinates, path segmentation step, receiving coordinates, and time sampling resolution; A replacement module is used to use the initialized parameters as the input of the LWPC model, and calculate the geomagnetic parameters, electronic parameters and neutral particle concentration of each segment point based on the IGRF model, the IRI model and the MSIS model, and then replace the corresponding parameters in the LWPC model; A calculation module, used for calculating the electron collision frequency of each ionosphere according to the electron parameter and the neutral particle concentration, and replacing the electron collision frequency in the LWPC model; A Fourier transform module, used for performing Fourier transform on the source waveform to obtain an amplitude spectrum and a phase spectrum of the source waveform; A superposition module is used to calculate the amplitude and phase changes of each frequency point along the propagation path based on the optimized LWPC model, and to superimpose the amplitude spectrum and phase spectrum of the source waveform with the amplitude and phase changes of the propagation path to obtain the amplitude spectrum and phase spectrum of the signal at the far-field receiving point; The inverse Fourier transform module is used to perform inverse Fourier transform on the amplitude spectrum and phase spectrum of the far-field receiving point signal to obtain a far-field time-domain simulation waveform.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the far-field electromagnetic pulse waveform simulation method as described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the far-field electromagnetic pulse waveform simulation method as described in any one of claims 1 to 7 is implemented.

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