Multi-level and multi-granularity simulation method for typical electromagnetic environment signals of RF detectors

Abstract

The present invention relates to a multi-level and multi-granularity simulation method for electromagnetic environment signals for radio frequency detectors. First, a radiation source simulation model, a scattering source simulation model, an interference simulation model, and a transmission weather simulation model for electromagnetic environment signal simulation are established respectively. The radiation source simulation model, the interference simulation model, and the transmission weather simulation model constitute a radiation source simulation subsystem. The scattering source simulation model, the interference simulation model, and the transmission weather simulation model constitute a scattering source simulation subsystem. The radiation source simulation subsystem and the scattering source simulation subsystem, as application software, run on a simulation basic platform to realize the performance simulation test interaction for radio frequency detectors. According to the real-time emission signal and motion attitude of the radio frequency detector, the radiation source simulation subsystem and the scattering source simulation subsystem output to the radio frequency detector for complex electromagnetic environment performance simulation tests, providing support for the performance simulation tests of radio frequency detectors. The simulation efficiency is high and the application prospect is broad.

Description

Technical Field

[0001] The present invention relates to the field of complex electromagnetic environment adaptability test and evaluation, and particularly relates to a multi-level and multi-granularity simulation method for typical electromagnetic environment signals for a radio frequency detector, which can be used for performance simulation tests of a radio frequency detector in a complex electromagnetic environment. Background Art

[0002] The electromagnetic characteristics of the target and its environment directly affect the target detection and recognition performance of the radio frequency detector, and are important factors in the performance test and evaluation of the radio frequency detector. In terms of the research on electromagnetic signal simulation, foreign scholars have continuously promoted the research on the basic algorithms of electromagnetic modeling and their engineering applications around the electromagnetic scattering calculations of targets such as electrically large targets, targets in complex environments, moving targets, and special structures. From the 1980s to the early 1990s, the focus was on the theoretical research of computational electromagnetic modeling tools and methods, and methods such as the method of moments, boundary element method, finite element method, and finite-difference time-domain method were formed. These methods have been used in commercial software or to establish models for specific problems; from the 1990s to the early 21st century, the focus was on the modeling ability for targets. To achieve "fast calculation and accurate calculation", mainly studied high-low frequency hybrid methods, domain decomposition calculation methods for multi-scale problems, fast interpolation calculation methods, parallel calculation methods, etc.; since the 21st century, mainly studied basic methods such as electromagnetic scattering calculations of targets in complex environments (mainly half-space environments), bistatic scattering calculations, combination of target characteristics and radar signal processing, electromagnetic scattering calculations of moving targets, and electromagnetic scattering calculations of special target structures. Based on the research of electromagnetic modeling algorithms, a variety of general and special electromagnetic modeling software have been designed and developed successively, realizing the engineering application ability of electromagnetic theory algorithms. The organic combination and mutual verification of experimental tests and theoretical modeling are the key ways to obtain accurate, real, and comprehensive target and environmental characteristic data and improve the practicality of models and data. Especially for natural environments, interference environments, etc., it is difficult to construct an accurate physical model representation. Based on experimental tests and theoretical model analysis, the use of data science methods is the main way to construct a mathematical model and obtain complete data. In terms of theoretical research, foreign countries have successively developed theoretical models such as analytical approximation methods and exact numerical methods. Each algorithm has different degrees of simplification in the description of natural environments and scattering mechanism models. Without strict verification, the engineering applicability is very limited. It is necessary to mutually verify the theoretical modeling data and measured data according to actual application requirements.

[0003] In China, many units represented by Beihang University, University of Electronic Science and Technology of China, Xidian University, etc. have carried out research on electromagnetic characteristic modeling technology. Numerous technological breakthroughs have been achieved, which are comparable to the overall foreign level, but there is still a certain gap from actual applications. Currently, the existing technologies have incomplete modeling elements and insufficient model verification. In particular, the integrated application of various interference strategies and models is lacking, making it difficult to form the ability to generate electromagnetic characteristic data of complex environments that is as consistent with the actual situation as possible, and there is a gap from the actual application requirements. Summary of the Invention

[0004] In order to solve the technical problems that it is difficult to simulate and measure the anti-interference ability, recognition ability, tracking ability, weather adaptability, etc. of radio frequency detectors in complex battlefield environments, the purpose of the present invention is to provide a multi-level and multi-granularity simulation method for typical electromagnetic environment signals for radio frequency detectors.

[0005] In order to achieve the above tasks, the present invention adopts the following technical solutions:

[0006] A multi-level and multi-granularity simulation method for typical electromagnetic environment signals for radio frequency detectors, characterized in that the method first separately establishes a radiation source simulation model, a scattering source simulation model, an interference simulation model, and a transmission weather simulation model for electromagnetic environment signal simulation; among them:

[0007] The radiation source simulation model, the interference simulation model, and the transmission weather simulation model constitute a radiation source simulation subsystem;

[0008] The scattering source simulation model, the interference simulation model, and the transmission weather simulation model constitute a scattering source simulation subsystem;

[0009] The radiation source simulation subsystem and the scattering source simulation subsystem, as application software, run on the simulation basic platform to realize the performance simulation test interaction of radio frequency detectors;

[0010] The simulation test interaction of the radiation source simulation subsystem and the scattering source simulation subsystem includes the following steps:

[0011] Step 1: The radiation source simulation model, the scattering source simulation model, the interference simulation model, and the transmission weather simulation model generate instances of their respective models according to the situation file generated by the situation design subsystem and initialize;

[0012] Step 2: The radiation source simulation model, the scattering source simulation model, and the interference simulation model respectively obtain the quantity and number information of the radiation source model instance, the scattering source model instance, and the related interference model instance;

[0013] Step 3: The transmission weather model instance obtains the atmospheric transmission loss calculated in real time according to the positional relationship between the radiation source, scattering source, interference device and the equipment during the simulation process;

[0014] Step 4: According to the simulation time beat, the radiation source model instance, scattering source model instance and the related interference model instance simulate and generate their respective independent signals, and then a signal synthesis simulation model is used for signal synthesis;

[0015] The target scattering characteristic data required in the scattering source simulation model is calculated offline to form a target characteristic database for use in the scattering source model simulation, which specifically includes radiation source signal simulation, scattering source signal simulation, ground background clutter signal simulation, interference simulation, transmission weather simulation and signal synthesis simulation.

[0016] Step 5: According to the real-time transmitted signal and motion attitude of the RF detector, the radiation source simulation subsystem and the scattering source simulation subsystem output to the RF detector for complex electromagnetic environment performance simulation tests.

[0017] According to the present invention, in the above step 4, the independent signals at least include radiation source simulation signals, active decoy interference simulation signals, scattering source simulation signals, and jamming, deception interference and passive interference simulation signals. Among them, the radiation source simulation signals and active decoy interference simulation signals need to modulate the atmospheric transmission attenuation, and are sent to the RF detector antenna through the signal synthesis model; the scattering source simulation signals, and jamming, deception interference and passive interference simulation signals, after modulating the atmospheric transmission attenuation, then modulate the antenna gain of the RF detector, and through the signal synthesis model, complete the antenna pattern modulation and signal coherent synthesis.

[0018] Furthermore, the simulation basic platform consists of a service logic layer, a service layer and a data layer. Among them, the radiation source simulation subsystem and the scattering source simulation subsystem are located in the service logic layer, the service layer is a simulation operation environment, including service components, middleware and operating systems, and the data layer is used for data storage, including disks and databases.

[0019] The multi-level and multi-granularity simulation method for typical electromagnetic environment signals for RF detectors according to the present invention, compared with the prior art, its innovation lies in:

[0020] 1. A signal simulation architecture for the adaptability, anti-jamming ability, recognition ability, tracking ability and weather adaptability performance boundaries of a typical complex electromagnetic environment for RF detectors is established, and the simulation of typical entities (including active radiation sources, targets and various interferences) and environmental characteristics is carried out, providing a scientific basic basis and reliable data source for countermeasure simulation tests.

[0021] 2. A general electromagnetic signal simulation test method is established. It is designed with multiple hierarchical structures such as the data layer, service layer, business logic layer, and model concatenation layer. Different models with different objectives adopt model design methods at different levels such as the function level and signal level, meeting the test requirements of the complex electromagnetic environment of radio frequency detectors. Description of the Drawings

[0022] Figure 1 It is a structural block diagram of the simulation basic platform for the multi-level and multi-granularity simulation method of typical electromagnetic environment signals for radio frequency detectors according to the present invention.

[0023] Figure 2 It is a flow block diagram of the radiation source signal simulation.

[0024] Figure 3 It is a flow block diagram of the scatterer signal simulation.

[0025] Figure 4 It is a flow block diagram of the ground background clutter signal simulation.

[0026] Figure 5 It is a flow block diagram of the interference signal simulation.

[0027] Figure 6 It is a flow block diagram of the transmission weather simulation.

[0028] Figure 7 It is a flow block diagram of the signal synthesis simulation.

[0029] The following further elaborates on the present invention in detail with reference to the drawings and embodiments. Detailed Implementation Manner

[0030] Refer to Figure 1 , this embodiment provides a multi-level and multi-granularity simulation method for typical electromagnetic environment signals for radio frequency detectors. First, a radiation source simulation model, a scatterer simulation model, an interference simulation model, and a transmission weather simulation model for electromagnetic environment signal simulation are established respectively;

[0031] The radiation source simulation model is used to generate target radiation source signals and provide simulation data support for radio frequency detectors; the scatterer simulation model solves the scattering characteristics of various targets and ground object backgrounds in the simulation scene through electromagnetic calculation methods and establishes a target scene scattering field database; the interference simulation model is used to simulate active decoys, active jammers, and passive interference sources, establish a model library containing various typical interferences, and generate interference simulation data as needed; the transmission weather simulation model models the attenuation law of electromagnetic wave energy for the transmission loss of radar signals under different weather conditions and outputs the atmospheric echo attenuation factor or the electromagnetic wave transmission loss coefficient.

[0032] In this embodiment, the radiation source simulation model, the interference simulation model, and the transmission weather simulation model constitute the radiation source simulation subsystem;

[0033] The scatterer simulation model, the interference simulation model, and the transmission weather simulation model constitute the scatterer simulation subsystem;

[0034] The radiation source simulation subsystem and the scatterer simulation subsystem, as application software, run on the simulation basic platform to realize the performance simulation test interaction of the RF detector;

[0035] In this embodiment, the simulation basic platform is composed of a business logic layer, a service layer, and a data layer. Among them, the radiation source simulation subsystem and the scatterer simulation subsystem are located in the business logic layer. The service layer is a simulation operation environment, including service components, middleware, and an operating system. The data layer is used for data storage, including disks and databases.

[0036] The simulation test interaction process of the radiation source simulation subsystem and the scatterer simulation subsystem is as Figures 2 to 7 shown and includes the following steps:

[0037] Step 1: The radiation source simulation model, the scatterer simulation model, the interference simulation model, and the transmission weather simulation model generate instances of their respective models according to the situation file generated by the situation design subsystem and initialize them;

[0038] Step 2: The radiation source simulation model, the scatterer simulation model, and the interference simulation model respectively obtain the quantity and number information of the radiation source model instance, the scatterer model instance, and the related interference model instance;

[0039] Step 3: The transmission weather model instance obtains the atmospheric transmission loss calculated in real time according to the position relationship between the radiation source, the scatterer, and the interference equipment and the equipment during the simulation;

[0040] Step 4: According to the simulation time beat, the radiation source model instance, the scatterer model instance, and the related interference model instance simulate and generate their respective independent signals, and then use the signal synthesis simulation model for signal synthesis;

[0041] In Step 4, the independent signals at least include radiation source simulation signals, active decoy interference simulation signals, scatterer simulation signals, and suppression, deception interference, and passive interference simulation signals. Among them, the radiation source simulation signals and the active decoy interference simulation signals need to be modulated by the atmospheric transmission attenuation, and after passing through the signal synthesis model, they are sent to the RF detector antenna; the scatterer simulation signals and the suppression, deception interference, and passive interference simulation signals are modulated by the atmospheric transmission attenuation and then modulated by the RF detector antenna gain. Through the signal synthesis model, the antenna pattern modulation and signal coherent synthesis are completed.

[0042] In step 4, the required target scattering characteristic data in the scattering source simulation model is calculated offline to form a target characteristic database for use in the scattering source model simulation.

[0043] Specifically, it includes:

[0044] Step 4-1: The radiation source signal simulation process is as Figure 2 shown, specifically:

[0045] 1) Receive the passive working mode start instruction sent by the RF detector and start the simulation;

[0046] 2) Conduct airspace division according to the radiation source type, location, task requirements, etc.;

[0047] 3) Conduct wave position arrangement in the airspace according to the antenna pointing and scanning method;

[0048] 4) Generate a radiation source search event linked list according to the wave position arrangement result;

[0049] 5) Event arrangement for the scheduling interval

[0050] In this step, the event arrangement for the scheduling interval is to arrange the radiation source signal irradiation events for one scheduling period according to the set scheduling interval strategy;

[0051] 6) Determine whether there is active interference in the model:

[0052] If there is active interference, generate an interference execution event linked list according to the start and end times of the current beat;

[0053] If there is no active interference, skip the step of generating the interference execution event linked list and directly proceed to step 7);

[0054] 7) Generate the execution event linked list;

[0055] 8) Take out the next irradiation event in the execution event linked list;

[0056] 9) Calculate the antenna gain of the RF detector

[0057] In this step, the calculation of the antenna gain of the RF detector is to calculate the antenna gain of the RF detector according to the irradiation direction of this irradiation event and the relative position relationship between the RF detector and the radiation source;

[0058] 10) Calculate the modulation parameters of the signal

[0059] In this step, the calculation of the modulation parameters of the signal is to calculate the modulation parameters of the transmitted signal according to the spatial geometric relationship, antenna gain, and signal transmission attenuation, and the modulation parameters include parameters such as power / amplitude, time delay, etc.;

[0060] 11) Generate transmitted signal samples

[0061] In this step, the generation of transmitted signal samples means generating the required transmitted signal samples of the radiation source by using the scheduled signal pattern and the calculated modulation parameters;

[0062] 12) Determine whether the beat ends:

[0063] If the beat does not end, return to step 8) to obtain the next irradiation event; if the beat ends, enter the judgment step for the end of the passive working mode simulation;

[0064] 13) Determine whether the passive working mode simulation ends:

[0065] If the passive working mode simulation does not end, return to step 7) and generate the transmitted signal samples of each event in sequence according to the above process.

[0066] If the passive mode simulation ends, exit.

[0067] Step 4-2: The simulation process of the scatterer signal is as Figure 3 shown, specifically:

[0068] 1) Receive the active working mode start instruction sent by the RF detector and start the simulation;

[0069] 2) Input the real-time parameter information of the scatterer

[0070] In this step, the real-time parameter information of the scatterer includes the position, velocity and other parameter information of the scatterer such as the target and ground objects;

[0071] 3) Input the radiation signal parameters of the RF detector

[0072] In this step, the detector radiation signal parameters include the position, velocity, radiation signal, etc. of the RF detector;

[0073] 4) Generate scatterer echo signal samples in parallel

[0074] In this step, the scatterer echo signal samples include narrowband echo signal samples, broadband echo signal samples and ground background echo signal samples;

[0075] 5) Output all the scatterer echo signal samples in step 4).

[0076] 6) Determine whether the active working mode ends. If the active working mode does not end, return to step 2) and repeat the operations from step 2) to step 5). If the active working mode ends, end and exit.

[0077] The implementation of the step of generating the echo signal sampling of the scattering source in parallel in step 4) above will be described below.

[0078] A. Generating narrowband echo signal sampling: It is to calculate the narrowband scattering characteristics and other modulation parameters of the target under the condition that the signal emitted by the RF detector is a narrowband signal, and generate the narrowband echo signal sampling.

[0079] For example, under narrowband conditions, the target can be regarded as a point target, and its scattering characteristics are characterized by RCS. For the simulation of the narrowband RCS of the target, two methods can be used: the interpolation method and the Swerling model.

[0080] 1. Interpolation method

[0081] In this method, it is necessary to use special electromagnetic calculation software offline to calculate the scattering characteristics of the target in all directions to form a table. In the simulation, the incident angle of the radio wave is calculated using the position of the RF detector, the position and attitude of the target, and the measured data is interpolated using the incident angle, frequency, polarization mode, etc. to obtain the required RCS value.

[0082] The implementation of this method requires electromagnetic calculation to calculate multi-dimensional scattering characteristic data such as azimuth angle, elevation angle, frequency, and polarization.

[0083] 2. Swerling model method

[0084] For relatively complex targets, according to the differences in the scanning period of the RF detector, the repetition frequency, the speed of change of the relative attitude of the target, and the statistical characteristics of the RCS fluctuation of the target, 4 types of Swerling models can be used to describe the RCS fluctuation law of the target.

[0085] 1) Swerling I and II fluctuation models

[0086] These two fluctuation models represent targets composed of many independent scattering units (but none of them play a decisive role). Among them, the Swerling I model is a slow fluctuation model (fluctuation between scans), and the Swerling II model is a fast fluctuation model (fluctuation between pulses). The received voltage envelope generated by these two fluctuation models can be described by Rayleigh statistics. Therefore, the target RCS, which is proportional to the square of this voltage, follows an exponential distribution, and its density function is:

[0087]

[0088] In the formula, σ is the radar cross section, that is, RCS; is the average value of RCS.

[0089] 2) Swerling III and IV fluctuation models

[0090] These two fluctuation models represent targets composed of a dominant non-fluctuating scatterer and a group of smaller independent scatterers. Among them, the Swerling III model is a slow fluctuation model (fluctuation between scans), and the Swerling IV model is a fast fluctuation model (fluctuation between pulses).

[0091] For the Swelling III and IV fluctuation models, it is assumed that the target RCS can be described by an X distribution with two degrees of freedom. Therefore, the probability density function of the target RCS is: 2 In the formula,

[0092]

[0093] where is the average value of the RCS.

[0094] In the above fluctuation models, a key quantity is included, that is, the average value of the RCS, which can be set by the user or given according to the results of electromagnetic calculations.

[0095] B. Generating broadband echo signal samples: This is to calculate the broadband scattering characteristics and other modulation parameters of the target under the condition that the signal emitted by the RF detector is a broadband signal, and generate broadband echo signal samples.

[0096] For example, under broadband conditions, the target can be equivalent to multiple strong scatterers. For the simulation of the target broadband scattering characteristics, two methods can be used: the electromagnetic calculation method and the scatter point model method.

[0097] 1. Electromagnetic calculation method

[0098] This method is similar to the narrowband scattering model and requires off-line calculation using specialized electromagnetic calculation software to form a scattering characteristic database.

[0099] The target scattering characteristic data needs to meet the imaging requirements of the RF detector. Under a certain incident angle, frequency, and polarization condition, according to the working bandwidth of the RF detector, it is calculated at multiple frequency points. On the premise of only considering the linear polarization of the incident wave, the finally calculated target scattering characteristic data is: for the same incident angle, working frequency, horizontal polarization and vertical polarization of the incident wave, finally obtain an RCS matrix with the preset number of frequency points. This matrix contains dual-polarization information, and each element in the matrix is a complex number containing amplitude and phase information.

[0100] During simulation, according to the real-time incident angle, frequency, polarization, etc., select the closest set of scattering data.

[0101] Several methods for calculating the target electromagnetic scattering characteristics are as follows:

[0102] a) Physical Optics (PO)

[0103] The physical optics method theory replaces the scatterer itself with the induced current on the surface of the scatterer, and obtains the scattered field through the approximation and integration of the surface induced field. Since the induced field is finite, the scattered field is also finite, thus overcoming the problem of infinite fields in the case of flat surfaces and single-curved surfaces.

[0104] The starting point of the physical optics method is the Stratton-Chu integral equation, and these expressions are correct for closed scattering surfaces. However, if the surface is not closed, certain additional terms (line integrals around the edges of the open surface) must be added to account for the edge discontinuities. In the high-frequency case, due to the interference and cancellation of the scattered fields, not the entire "bright region" contributes to the scattered field. In fact, only the induced current near the specular reflection point (commonly called within the first Fresnel zone) makes a substantial contribution to the scattered field, and the contributions of the scattered fields in other places can be ignored.

[0105] b) Geometrical Optics (GO)

[0106] The basic principle of the Geometrical Optics (GO) is to use classical ray tubes to explain the scattering mechanism and energy propagation, which can be regarded as a high-frequency approximation of Maxwell's equations when the electromagnetic wave wavelength λ→0. The Geometrical Optics method believes that in the high-frequency case, the energy of the electromagnetic wave propagates around the ray tube, so this method is also called the ray optics method.

[0107] c) Shooting and Bouncing Rays (SBR)

[0108] The Shooting and Bouncing Rays (SBR) is a hybrid method based on GO and PO. GO is used to calculate the multiple reflections of electromagnetic waves between different parts of the target, and to some extent, it considers the coupling effect between different parts of the target. PO is responsible for calculating the scattered field of the target, overcoming the limitation that GO is only applicable to smooth targets with doubly curved surfaces. SBR combines the respective advantages of GO and PO, and its numerical accuracy is usually higher than that of other high-frequency approximation methods. SBR was first used to calculate the scattering of cavities, and its ability to calculate multiple reflections was specifically designed for simulating the propagation of electromagnetic waves in cavities. Later, SBR was extended to the electromagnetic scattering calculation of general targets with arbitrarily complex shapes. For most electrically large and complex targets, SBR only needs to be used in combination with a method that can calculate the edge diffraction effect to achieve the required accuracy.

[0109] 2. Scattering Point Model Method

[0110] In the high-frequency region, the total electromagnetic scattering of a target can be considered as the synthesis of electromagnetic scattering at some local positions. These local scattering sources are usually called scattering centers. The existence of target scattering centers is one of the basic characteristics of target scattering in the high-frequency region. When using broadband signals, the distribution information of target scattering centers in the radial distance can be obtained, which is the range profile; if the Doppler information of a moving target is utilized, the distribution of scattering centers in the cross-range can be obtained. By using imaging algorithms, the distribution of target scattering centers in a two-dimensional plane can be obtained. The objective existence of scattering centers is the theoretical basis for simulating target characteristics with N scattering points.

[0111] Testing the broadband characteristics of a target requires a lot of manpower and material resources, and has rather strict requirements for test conditions, and its acquisition is relatively difficult. In the case where real measurement data is difficult to obtain, adopting an equivalent method to equivalent the target as an integration of multiple scattering centers is a relatively simple and feasible method.

[0112] The strength and spatial position distribution of target scattering centers mainly depend on the characteristics of the target scattering points to be simulated. According to the theory of electromagnetics, the main types of target scattering centers are as follows: specular scattering centers, edge scattering centers, tip scattering centers, multiple scattering types such as concave cavities, traveling waves and creeping waves, antenna-type scattering, etc.

[0113] C. The generation of ground background echo signal sampling is for the ground background clutter signal of the RF detector, and is obtained by successively performing range, Doppler cell division, single resolution cell echo generation, and combination of multiple cell echoes.

[0114] For example, the coherent clutter model utilizes the phase of the clutter, contains all the information about the radar environment, and can simulate the entire detection process that the actual RF detector has to perform.

[0115] 1. Ground scattering cell division model

[0116] The division of ground scattering cells should satisfy that the antenna gain, Doppler frequency shift, range, incident angle, clutter reflectivity (these parameters are related to the clutter echo) of each scattering cell are constants. Here, it is assumed that the clutter is uniform, that is, the backscattered signals from different scattering cells are statistically independent and have no coherence in space. Under this assumption, the calculation of the clutter signal can be simplified to the coherent superposition of the echo signals of each scattering cell. The division of ground scattering cells is carried out according to azimuth and range resolution, and the cell range interval is ρ x , and the azimuth interval is ρ y .

[0117] 2. Coherent clutter signal model

[0118] Coherent clutter is the coherent superposition of the echo signals of all clutter scattering cells. Therefore, it is necessary to first determine the echo signal of a scattering cell. A scattering cell is regarded as a point scatterer. According to the radar equation, the amplitude of the echo signal of the scattering cell at (m,n) received by the RF detector can be expressed as:

[0119]

[0120] where m and n represent the sequence numbers in the azimuth and range directions of the cell grid, P t is the peak power of the signal transmitted by the RF detector, λ is the operating wavelength of the RF detector, σ is the radar cross section of this scattering cell, G(α T , β T ) is the voltage gain of the RF detector antenna, α T , β T are the azimuth angle and elevation angle of this clutter scattering cell in the antenna coordinate system, L is the combined transmission and reception loss of the RF detector, and R(m,n) is the distance from the RF detector to the center of this scattering cell.

[0121] The Doppler phase of the echo signal of the scattering cell at (m,n) can be expressed as:

[0122]

[0123] where R(m,n) is the distance from the RF detector to the center of this scattering cell, and λ is the operating wavelength of the RF detector.

[0124] Considering the form of the signal transmitted by the RF detector, the echo signal of a single scattering cell is obtained as:

[0125]

[0126] where m and n represent the sequence numbers in the azimuth and range directions of the cell grid, A(m,n) is the amplitude of the echo signal, ψ(m,n,t) is the Doppler phase of the echo signal at time t, is the phase determined by the waveform of the pulse signal transmitted by the RF detector, and φ0 is a random initial phase that satisfies a uniform distribution.

[0127] For the RF detector, for a given clutter type, signal frequency, and polarization, the backscattering coefficient σ 0 is related to the incident angle.

[0128] Its mathematical model includes both relatively simple empirical models and more complex theoretical models. For computer simulation, to reduce the amount of computation, an empirical model is generally used. The average backscattering coefficient model for each scattering cell adopts a modified equal-γ model:

[0129]

[0130] wherein, σ od , σ os , φ0 are deterministic quantities, β s is the grazing angle, the first term on the right side is the diffuse component, and the second term is the specular reflection component. The latter constitutes the height echo of the RF detector, and φ0 is the angular width of the specular reflection component.

[0131] The radar cross section of the clutter scattering cell is:

[0132] σ F (m,n) = σ 0 (m,n)ρ x ρ y

[0133] wherein, m and n represent the sequence numbers of the azimuth and range directions of the unit grid, and σ 0 (m,n) is a random number subject to Rayleigh distribution (or Gaussian distribution), and the mean value is ρ x and ρ y are the radar azimuth and range resolutions respectively.

[0134] 3. Signal coherent superposition model

[0135] Generate the echo signals corresponding to the grids point by point and coherently superpose them to form the ground background echo signal model under this pulse:

[0136]

[0137] wherein, M and N are the numbers of unit grid divisions in the azimuth and range directions respectively, m and n represent the sequence numbers of the azimuth and range directions of the unit grid, t represents the signal time, s(m,n,t) represents the signal in a single grid division, and s(t) is the entire ground background echo signal after superposition of all grid divisions.

[0138] Step 4-3. The simulation process of the ground background clutter signal is as Figure 4 shown, specifically:

[0139] 1) First, when entering the ground background clutter simulation model each time, judge whether this frame of data is the initial data frame of the data packet;

[0140] 2) If this frame is the initial data frame of the data packet, it is necessary to calculate the position where the beam center of the first pulse in this data frame irradiates on the ground; if this frame is not the initial data frame of the data packet, directly enter the step of calculating the corresponding antenna gain point by point and its subsequent steps;

[0141] 3) Obtain the coordinates where the beam center irradiates on the ground, and use these coordinates as the center of the grid matrix;

[0142] 4) Calculate the geographical locations of each grid with the beam center as the center of the grid matrix

[0143] The specific implementation process is as follows: Initialize the grid matrix according to the beam irradiation area and two-dimensional resolution, and calculate the maximum area scanned by the beam during the simulation process based on parameters such as the slant range, incident angle, azimuth and elevation angle ranges, and imaging resolution in different operating modes of the RF detector. The total grid area is required to be slightly larger than the beam scanning area, and the distance between adjacent grids is determined according to the resolution in different modes;

[0144] 5) Calculate the antenna gain corresponding to each grid point by point

[0145] The specific implementation process is as follows: Calculate the grid matrix data. The backscattering coefficient of the ground background noise is generated based on the statistical characteristics of the Gaussian distribution, and the scattering grid matrix of the radiation source is generated according to the azimuth and two-dimensional resolution of the grid as follows:

[0146] σ F (m,n) = σ 0 (m,n)ρ x ρ y

[0147] In the formula, σ 0 (m,n) represents a random number subject to the Rayleigh distribution (or Gaussian distribution), ρ x and ρ y are the radar azimuth and range resolutions respectively.

[0148] Traverse the grid, calculate the antenna gain corresponding to this grid position, and calculate the echo amplitude of the grid point under this pulse according to the radar cross-sectional area data of the grid radiation source. The calculation of the amplitude is based on the radar equation as follows:

[0149]

[0150] In the formula, P t is the peak power of the RF detector's transmitted signal, λ is the operating wavelength of the RF detector, σ is the radar cross-sectional area of this scattering unit, G(α T , β T ) is the antenna voltage gain of the RF detector, α T , β T are the azimuth angle and elevation angle of this clutter scattering unit in the antenna coordinate system, L is the combined transmission and reception loss of the RF detector, and R(m,n) is the distance from the RF detector to the center of this scattering unit.

[0151] 6) Generate the echo corresponding to each grid point by point and superimpose the echo signals

[0152] The specific implementation process is as follows: According to the signal model of the transmitted signal, the echo signals corresponding to the grids are generated point by point, and calculated according to the signal coherent superposition model to form the ground background echo signal under this pulse.

[0153] According to this ground background echo signal model, the background echo data under all pulses within a scheduling period are generated.

[0154] 7) Determine whether the traversal of the grid is completed

[0155] If so, enter the step of determining whether the traversal of the pulses is completed; if not, return to step 5);

[0156] 8) Determine whether the traversal of the pulses is completed

[0157] If so, end and exit; if not, return to step 1) and repeat the above process.

[0158] Step 4-4: The interference signal simulation process is as Figure 5 shown, specifically:

[0159] 1) Receive the active / passive working mode start instruction sent by the RF detector and start the simulation;

[0160] 2) Set the real-time parameter information of the jammer

[0161] The jammer includes various interference entities such as active decoys, active jammers, and passive interference bodies;

[0162] The real-time parameter information includes position, speed, attitude, etc.;

[0163] 3) Set the radiation parameters of the RF detector

[0164] The radiation parameters of the RF detector include parameters such as frequency, pulse width, bandwidth, and repetition period;

[0165] 4) Generate interference echo signal samples in parallel

[0166] The generation of the interference echo signal samples includes: active decoy radiation signal sampling, active suppression interference signal sampling, active deception interference signal sampling, and passive interference body echo signal sampling, where:

[0167] The active decoy interference signal sampling is to calculate the radiation signal parameters of the radiation source, calculate the delay of the interference relative to the radiation signal of the radiation source, and generate the decoy radiation signal sampling.

[0168] The active suppression interference signal sampling is to calculate the suppression interference parameters, generate white noise signal sampling, and perform interference parameter modulation or corresponding filtering processing on the white noise signal to generate.

[0169] The sampling of the active deception interference signal is the sampling of the active deception interference signal generated by simulating the signal emitted by the radio frequency detector and calculating the deception interference modulation parameters.

[0170] The sampling of the passive interference body echo signal is generated by calculating the incident angle of the passive interference body's radio wave and calculating the RCS of the passive interference body.

[0171] 5) Output all the sampled interference echo signals;

[0172] 6) Determine whether the active / passive mode has ended

[0173] If the active / passive mode has not ended, return to step 2) and continue the above operations; otherwise, end and exit.

[0174] The following are examples of specific implementations given by the inventor.

[0175] Sampling of active decoy interference signal: It is the sampling of the decoy radiation signal generated by calculating the radiation signal parameters of the radiation source and calculating the delay of the interference relative to the radiation signal of the radiation source; in the simulation, the radiation signal of the active decoy is obtained by appropriately delaying the emission signal of the radio frequency detector and modulating a certain Doppler.

[0176] Sampling of active suppression interference signal: It is generated by calculating the suppression interference parameters (frequency, bandwidth, power, etc.), generating white noise signal sampling, and performing interference parameter modulation or corresponding filtering processing on the white noise signal; the calculation formulas and methods are as follows:

[0177] 1. Wideband blocking noise interference model

[0178] The interference bandwidth of wideband blocking noise interference is very wide. It can be composed of several interference transmitters to form an interference source. The frequency bands of each interference transmitter are connected to each other to form a very wide total bandwidth, generally from dozens of megahertz to hundreds of megahertz. This kind of interference can suppress several radio frequency detectors with different operating frequencies at the same time. However, due to the wide interference bandwidth and power dispersion, only by increasing the interference power can good interference effects be achieved.

[0179] Wideband blocking noise interference generally satisfies:

[0180] Δf j >5Δf r ,f s ∈[f j -Δf j / 2,f j +Δf j / 2]

[0181] Among them, f j is the center frequency of the interference signal, and Δf j is the spectrum width of the interference signal, fs is the center frequency of the RF detector receiver, and Δf r is the receiver bandwidth.

[0182] From the interference equation, the interference power reaching the front end of the RF detector receiver is:

[0183]

[0184] In the formula, P j is the transmitting power of the jammer; G j is the gain of the jammer antenna in the direction of the RF detector; G l is the gain of the RF detector antenna in the direction of the jammer; λ is the operating wavelength of the RF detector; R j is the distance between the RF detector and the jammer; L j is the total transmitting loss; L r is the total receiving loss; L Atm is the atmospheric loss; f B is the bandwidth ratio factor.

[0185] 2. Swept-frequency noise interference model

[0186] Swept-frequency noise interference periodically changes the interference frequency within the entire interference frequency band at a certain tuning speed, so that all RF detectors within the interference frequency band can be suppressed by high power. By appropriately selecting the swept frequency speed of the jammer, the sensitivity of the RF detector receiver being interfered with cannot fully recover between two interference effects, or cause the RF detector screen to flicker.

[0187] Swept-frequency interference generally satisfies:

[0188] Δf j =(2 - 5)Δf r , f j =f s ·t, t ∈ [0, T]

[0189] where, f j is the center frequency of the interference signal, and Δf j is the spectrum width of the interference signal. f s is the center frequency of the RF detector receiver, and Δf r is the receiver bandwidth.

[0190] Therefore, the center frequency of the interference is a continuous time function with a period of T.

[0191] Swept-frequency noise interference can form intermittent periodic strong interference on the RF detector. The swept frequency range is relatively wide, and it can also interfere with frequency diversity, frequency agility, and multiple RF detectors with different operating frequencies.

[0192] It can be seen from the interference equation that the interference power reaching the front end of the RF detector receiver is as follows:

[0193]

[0194] In the formula, P j is the transmitting power of the jammer; G j is the gain of the jammer antenna in the direction of the RF detector; G l is the gain of the RF detector antenna in the direction of the jammer; λ is the operating wavelength of the RF detector; R j is the distance between the RF detector and the jammer; L j is the total transmitting loss; L r is the total receiving loss; L Atm is the atmospheric loss.

[0195] Sampling of active deception interference signals: Simulation of the signals transmitted by the RF detector, calculation of the deception interference modulation parameters (drawing rate, time, etc.), and generation of the deception interference signal sampling. The calculation formulas and methods are as follows:

[0196] 1. Range gate pull-off interference

[0197] Range gate pull-off interference (RGPO) is a main means of distance deception for the RF detector. The false target distance function R f (t) can be expressed by the following formula:

[0198]

[0199] In the formula, v is the pulling speed, a is the pulling acceleration, t1 is the time of the stop-pulling period, t2 is the time of the pulling period, and T J is the time of the stop period.

[0200] Under the condition of self-defense interference, R is also the distance where the target is located.

[0201] Converting the above formula into the forwarding delay Δtf of the jammer for the received RF detector irradiation signal, the forwarding delay Δt f of the range gate pull-off interference is:

[0202]

[0203] In the formula, v is the pulling speed, a is the pulling acceleration, t1 is the time of the stop-pulling period, t2 is the time of the pulling period, and T J is the time of the stop period.

[0204] The maximum pulling distance R max (or the maximum forwarding delay) is:

[0205]

[0206] In the formula, v is the towing speed, a is the towing acceleration, t1 is the time of the towing stop period, and t2 is the time of the towing period.

[0207] The specific working process of range gate towing jamming is as follows: within the towing stop time period [0, 1], the false target and the real target appear approximately coincident in space and time, and it is easy for the RF detector to detect and capture. Since the energy of the false target is higher than that of the real target, the ranging center of gravity of the RF detector tends to the false target. After entering the towing period, the false target gradually deviates from the real target in terms of distance, and the center of the range tracking gate of the RF detector also deviates from the real target along with the deviation of the false target; afterwards, the false target suddenly "disappears" and the tracking of the RF detector is suddenly interrupted.

[0208] The time length of the towing stop time period corresponds to the time required for the RF detector to detect and capture the target, the length of the towing time period depends on the maximum towing distance, and the length of the closing time depends on the residence and adjustment time after the tracking interruption of the RF detector.

[0209] The specific functional algorithm is as follows:

[0210] The range gate towing jamming is divided into an interference stop period and an interference period. When in the stop period, no interference signal is generated. The interference period is divided into a towing period and a non-towing period. When in the non-towing period, an interference signal identical to the signal of the RF detector is transmitted.

[0211] Assume the signal form is:

[0212]

[0213] In the formula, U j is the amplitude of the interference signal, ω j is the center frequency of the signal of the RF detector. is the phase of the signal of the RF detector.

[0214] When in the towing period, there is a time delay of Δt j (t) between the interference signal and the real signal of the RF detector, and the transmitted signal is:

[0215]

[0216] In the formula, U j is the amplitude of the interference signal, ω j is the center frequency of the signal of the RF detector, is the phase of the signal of the RF detector.

[0217] When the maximum towing distance is reached, the generation of the interference signal stops and the interference stop period is entered.

[0218] (2) Velocity gate towing jamming

[0219] The velocity gate pulling interference is used to interfere with the velocity measurement and tracking system of a radio frequency detector, aiming to create a false or incorrect velocity information for the radio frequency detector.

[0220] The basic principle of the velocity gate pulling interference is as follows: First, a jamming signal with the same Doppler frequency f as the target echo is forwarded, and the energy of the jamming signal is greater than that of the target echo. The velocity tracking circuit of the radio frequency detector can capture the Doppler frequencies f of the target and the interference. d The AGC circuit controls the gain of the radio frequency detector receiver according to the energy of the jamming signal. This period is called the stop-pulling period. Then, the Doppler frequency f of the jamming signal is gradually separated from the Doppler frequency of the target echo, and the separation speed v d .(Hz / s) is not greater than the maximum acceleration α of the radio frequency detector that can track the target, that is: dJ f dJ dJ

[0221]

[0222] where λ is the operating wavelength of the radio frequency detector.

[0223] Since the interference energy is greater than that of the target echo, the velocity tracking circuit of the radio frequency detector will track on the Doppler frequency f of the interference, dJ resulting in an incorrect velocity information. This period becomes the pulling period, and the time length (t2 - t1) is calculated according to the maximum frequency difference δf between f dJ and f d : max

[0224]

[0225] When the frequency difference δf = f between f dJ and f d reaches δf dJ d max dJ

[0226] the jammer is turned off.

[0226] Since the tracked signal suddenly disappears, and the disappearance time is greater than the waiting time of the radio frequency detector velocity tracking circuit and the recovery time of the AGC circuit, the velocity tracking circuit will re-enter the search state.

[0227] The change process of the Doppler frequency f of the velocity gate pulling interference signal is as follows: dJ

[0228]

[0229]

[0230] The specific functional algorithm is as follows:

[0230] The velocity gate pulling interference is divided into an interference stop period and an interference period. During the stop period, no interference signal is generated. The interference period is divided into a pulling period and a non-pulling period. During the non-pulling period, an interference signal identical to the radio frequency detector signal is transmitted. Assume the signal form is:

[0231]

[0232] where, f j is the center frequency of the radio frequency detector signal. is the phase of the radio frequency detector signal, and f d is the Doppler frequency of the radio frequency detector signal.

[0233] During the pulling period, there is a frequency shift of f dj (t) between the interference signal and the true signal of the radio frequency detector, and the transmitted signal is:

[0234]

[0235] where, f j is the center frequency of the radio frequency detector signal. is the phase of the radio frequency detector signal, and f d is the Doppler frequency of the radio frequency detector signal.

[0236] When the maximum pulling frequency is reached, the generation of the interference signal stops and the interference stop period is entered.

[0237] 3. Angle deception interference

[0238] Angle deception interference is mainly two-point source interference, including non-coherent interference and coherent interference.

[0239] 1) Non-coherent interference

[0240] Non-coherent interference is to set two or more interference sources within the resolution angle of the radio frequency detector, and there is no stable relative phase relationship (non-coherent) between the interference signals. The principle of non-coherent interference in a single plane is as follows:

[0241] The signals received by the receiving antennas 1 and 2 of the radio frequency detector from two interference sources J1 and J2 are respectively:

[0242]

[0243]

[0244] In the formula, A j1 , A j2 are respectively the amplitudes of the interference signals, ω1, ω2, They are the frequencies and initial phases of two interference sources respectively. θ represents the direction of signal arrival and the angle between the direction of the equal-strength signal of Antenna 1, Antenna 2, etc. Δθ represents the included angle between the arrival directions of Jammer 1 and Jammer 2 to the center of the antenna, and θ0 represents the included angle between the direction of the equal-strength signal and the center direction of Antenna 1 and Antenna 2.

[0245] The following three usage methods can be derived:

[0246] a) Synchronous flashing interference

[0247] Cooperated by J1 and J2, the jammers are turned on and off alternately, so that the power ratio of J1 and J2 changes according to the period T:

[0248]

[0249] In the formula: K represents a natural number starting from 0, and T represents the flashing period.

[0250] The time of the period T is 1 s to 6 s. The synchronous flashing interference causes the pointing of the tracking antenna of the RF detector to swing back and forth between J1 and J2. In addition to the cooperation between J1 and J2, the cooperation between the target and the nearby jammer can also be adopted. Since the interference power is much greater than the target echo, as long as the jammer is turned on and off periodically, the effect of synchronous flashing interference can also be achieved, and the requirement of synchronous cooperation is simplified.

[0251] b) Misleading interference

[0252] Cooperated by the jammer group Distributed in the predetermined misleading direction, the included angle of any two adjacent jammers to the RF detector is less than the angular resolution of the RF detector. When implementing the interference, first turn on the jammer to induce the RF detector to track J1, then turn on J2 to induce the radar to track the centroid of J1 and J2; then turn off J1 to induce the RF detector to track J2, and then turn on J3,... and so on until J n Turn off to induce the RF detector to track to the predetermined misleading direction. The misleading interference is mainly used to protect important targets from the attack of the RF detector.

[0253] c) Asynchronous flashing interference

[0254] J1 and J2 alternately turn on and off the jammer according to their respective control logics. Since J1 and J2 are turned on and off asynchronously, the following four combined states will be formed:

[0255] J1 and J2 work simultaneously, inducing the RF detector to track the energy centroid of J1 and J2.

[0256] J1 and J2 are both turned off, and the tracking signal of the RF detector disappears, and then it turns to re-capture the target.

[0257] J1 works, J2 is off, inducing the RF detector to track J1.

[0258] J2 works, J1 is off, inducing the RF detector to track J2.

[0259] The above four states are equally probable and randomly variable; the tracking state of the RF detector will be directly affected by the above states and cannot accurately track the target.

[0260] 2) Coherent interference

[0261] If the signals of J1 and J2 reaching the antenna aperture plane of the RF detector have a stable phase relationship (phase coherence), it is called coherent interference. Let be the phase difference between the signals of J1 and J2 at the RF detector antenna. The signals received by the receiving antennas 1 and 2 of the RF detector from the two jammers are respectively:

[0262]

[0263]

[0264] In the formula: A j1 , A j2 are respectively the amplitudes of the interference signals, θ represents the angle between the signal arrival direction and the equal-strength signal direction of antennas 1 and 2, Δθ represents the included angle between the jammers 1 and 2 reaching the center of the antenna, θ0 represents the included angle between the equal-strength signal direction and the center of antennas 1 and 2, represents the phase difference between the jammers 1 and 2, and ωt is the phase generated by the interference signal pattern.

[0265] Sampling of passive interference signals: Calculate the incident angle of the radio wave of the passive interference body, calculate the RCS (Radar Cross Section) of the passive interference body, and generate the sampling of the echo signal of the passive interference body; among them, the incident angle of the radio wave is calculated according to the position and attitude of the passive interference body and the position of the RF detector, and the RCS of the passive interference body is calculated according to the scattering characteristics of the passive interference body. The calculation formula and method are as follows:

[0266] Passive interference bodies usually include three types: square plate corner reflector, circular plate corner reflector, and triangular plate corner reflector. When simulating the corner reflector, mainly simulate its scattering characteristics, that is, RCS. No matter which type of corner reflector it is, it maintains a relatively stable and large RCS within a certain angle range (the included angle with the axis), and is relatively small outside the angle range. Therefore, when simulating the characteristics of the corner reflector, mainly focus on three key parameters, namely the maximum RCS, the half-power point width (the angle corresponding to when the RCS drops to half of the maximum value), and the full-attitude average RCS.

[0267] 1. Square plate corner reflector

[0268] The maximum RCS of a square plate corner reflector can be calculated by the following formula:

[0269] RCS max = 12πb 4 / λ 2

[0270] where b is the side length and λ is the wavelength.

[0271] The half-power beamwidth of a square plate corner reflector is generally 25°.

[0272] The full-attitude average RCS of a square plate corner reflector can be calculated by the following formula:

[0273] RCS max = 0.7b 4 / λ 2

[0274] 2. Circular plate corner reflector

[0275] The maximum RCS of a circular plate corner reflector can be calculated by the following formula:

[0276] RCS max = 15.6b 4 / λ 2

[0277] The half-power beamwidth of a circular plate corner reflector is generally 32°.

[0278] The full-attitude average RCS of a circular plate corner reflector can be calculated by the following formula:

[0279] RCS max = 0.47b 4 / λ 2

[0280] 3. Triangular plate corner reflector

[0281] The maximum RCS of a triangular plate corner reflector can be calculated by the following formula:

[0282] RCS max = 4πb 4 / (3λ 2 )

[0283] The half-power beamwidth of a triangular plate corner reflector is generally 40°.

[0284] The full-attitude average RCS of a triangular plate corner reflector can be calculated by the following formula:

[0285] RCS mean = 0.17b 4 / λ 2 .

[0286] Step 4-5: The transmission weather simulation process is as follows Figure 6 shown, specifically:

[0287] 1) Receive the active / passive mode start instruction of the RF detector and start the simulation;

[0288] 2) Input the position information of both the electromagnetic wave transceiver sides, that is, the positions of the RF detector and the equipment or environmental factors at both ends of the electromagnetic wave propagation such as the radiation source and the target;

[0289] 3) Calculate the angle and distance of the electromagnetic wave propagation according to the position;

[0290] 4) Select the polynomial fitting coefficients corresponding to the angle;

[0291] The implementation process is to select the polynomial fitting coefficients of the tropospheric refraction loss, tropospheric absorption loss, cloud / rain / fog / haze environment transmission loss, etc. corresponding to the angle according to the angle of the electromagnetic wave propagation;

[0292] 5) Calculate the propagation loss using the polynomial;

[0293] 6) Output the propagation loss value;

[0294] 7) Judge whether the active / passive mode ends

[0295] If the active / passive mode ends, end the simulation, otherwise return to step 2) to continue the process.

[0296] Step 4-6: The signal synthesis simulation process is as follows Figure 7 shown, specifically:

[0297] 1) Receive the active mode start instruction of the RF detector and start the simulation;

[0298] 2) Input the antenna parameters or data of the RF detector

[0299] The antenna parameters refer to the antenna pattern parameters of the RF detector, and the antenna data refers to the antenna pattern measurement data;

[0300] 3) Calculate the antenna gain in the direction of the incoming electromagnetic wave;

[0301] 4) Modulate the amplitude and phase of the multi-channel for each scattered echo signal sampling;

[0302] 5) Perform coherent superposition of the echoes in the same channel

[0303] This step refers to sampling the modulated scattered echo signals and performing coherent superposition of the echoes in the same channel to form the final output signal sampling;

[0304] 6) Judge the end of the active mode

[0305] If the active mode ends, the simulation ends; otherwise, return to step 2) to continue the process.

[0306] Step 5: According to the real-time transmitted signal and motion attitude of the RF detector, the radiation source simulation subsystem and the scattering source simulation subsystem output to the RF detector for complex electromagnetic environment performance simulation tests.

[0307] In summary, this embodiment presents a typical complex electromagnetic environment multi-level and multi-granularity simulation method and model for RF detectors, with strong applicability. The electromagnetic environment signal model is formed by combining simulation models of different granularities, and a typical complex electromagnetic environment simulation signal generation system is gradually constructed based on the hierarchical simulation modeling method. The model has strong friendliness and scalability, is designed for engineering applications, and can provide support for the performance simulation tests of RF detectors. It provides a technical approach for the simulation modeling of target signals, interference signals, and background signals in the typical complex electromagnetic environment of RF detectors, meeting the requirements of the complex electromagnetic environment tests of RF detectors. At the same time, it has good scalability and high simulation efficiency.

Claims

1. A multi-level and multi-granularity simulation method for typical electromagnetic environment signals for radio frequency detectors, characterized in that, This method first separately establishes a radiation source simulation model, a scattering source simulation model, an interference simulation model, and a transmission weather simulation model for electromagnetic environment signal simulation; where: The radiation source simulation model, the interference simulation model, and the transmission weather simulation model constitute a radiation source simulation subsystem; The scattering source simulation model, the interference simulation model, and the transmission weather simulation model constitute a scattering source simulation subsystem; The radiation source simulation subsystem and the scattering source simulation subsystem, as application software, run on the simulation basic platform to realize the performance simulation test interaction of the radio frequency detector; The simulation test interaction of the radiation source simulation subsystem and the scattering source simulation subsystem includes the following steps: Step 1: The radiation source simulation model, the scattering source simulation model, the interference simulation model, and the transmission weather simulation model generate instances of their respective models according to the situation file generated by the situation design subsystem and initialize; Step 2: The radiation source simulation model, the scattering source simulation model, and the interference simulation model respectively obtain the quantity and number information of the radiation source model instance, the scattering source model instance, and the related interference model instance; Step 3: The transmission weather model instance obtains the atmospheric transmission loss calculated in real time according to the position relationship between the radiation source, the scattering source, and the interference device and the equipment during the simulation; Step 4: According to the simulation time beat, the radiation source model instance, the scattering source model instance, and the related interference model instance simulate and generate their respective independent signals, and then use the signal synthesis simulation model for signal synthesis; Among them, the target scattering characteristic data required in the scattering source simulation model is calculated offline to form a target characteristic database for the scattering source model simulation; specifically including radiation source signal simulation, scattering source signal simulation, ground background clutter signal simulation, interference simulation, transmission weather simulation, and signal synthesis simulation; Step 5: According to the real-time emission signal and motion posture of the radio frequency detector, the radiation source simulation subsystem and the scattering source simulation subsystem output to the radio frequency detector for complex electromagnetic environment performance simulation test.

2. The method according to claim 1, characterized in that, In the above step 4, the independent signals at least include radiation source simulation signals, active decoy interference simulation signals, scattering source simulation signals, and suppression, deception interference, and passive interference simulation signals. Among them, the radiation source simulation signals and the active decoy interference simulation signals need to modulate the atmospheric transmission attenuation and are sent to the radio frequency detector antenna through the signal synthesis model; the scattering source simulation signals and the suppression, deception interference, and passive interference simulation signals modulate the atmospheric transmission attenuation and then modulate the radio frequency detector antenna gain, and through the signal synthesis model, complete the antenna pattern modulation and signal coherent synthesis.

3. The method according to claim 1, characterized in that, The simulation basic platform consists of a business logic layer, a service layer, and a data layer. Among them, the radiation source simulation subsystem and the scattering source simulation subsystem are located in the business logic layer. The service layer is a simulation operation environment, including service components, middleware, and an operating system. The data layer is used for data storage, including disks and databases.

Images