CN115270590A - A real-time simulation method for multi-granularity modeling of communication systems in adversarial simulation - Google Patents

Abstract

The invention discloses a multi-granularity modeling real-time simulation method for a communication system in countermeasure simulation, which constructs engineering-level, functional-level and task-level models of a military communication system. For scenes with high requirements on fineness, professional electromagnetic simulation software is used for resolving antenna data of communication equipment in an off-line mode, and accurate data are obtained in real time through on-line interpolation during simulation operation; for scenes with low fineness requirements, typical parameters are adopted to describe the directivity of the antenna; for large-scale military communication networks, the real-time performance requirement is higher, so that the antenna directivity is not considered, and only the communication coverage is considered. In addition, battlefield communication interference and atmospheric and terrain visibility problems are considered in the modeling process. The invention finally establishes a set of multi-granularity models from antenna solution, link simulation to military network communication, and introduces a communication system modeling device facing countermeasure simulation of the influence of the battlefield environment on the communication.

Description

A real-time simulation method for multi-granularity modeling of communication systems in countermeasure simulation

technical field

The invention relates to the technical field of combat simulation and multi-granularity modeling of battlefield communication systems, in particular to a real-time simulation method for multi-granularity modeling of communication systems in countermeasure simulation.

Background technique

The historical development of war is closely related to the development of military communication systems, from the earliest primitive communication systems such as beacon warnings to today's military communication systems. With the development of science and technology, informatization has become one of the important indicators of today's military combat effectiveness, and the modeling and simulation of communication systems oriented to confrontation simulation is an important research direction for evaluating military informatization.

The communication system is a very complex system, how to model it accurately and meet the real-time requirements is a problem worth studying. Establishing models with different granularities to describe and analyze is a very effective means to deal with complex problems, and can effectively solve the problems of model sophistication and simulation real-time performance. For the modeling and simulation of communication systems, the use of multi-granularity modeling can solve the contradiction between the fineness of the model and the real-time simulation, so it is necessary to study the multi-granularity modeling of communication systems.

Multi-granularity modeling has become a research hotspot in the field of modeling and simulation. Although there are still many problems to be solved in theory and technology of multi-granularity modeling, the importance of multi-granularity modeling technology in distributed simulation has been shown. Carrying out research on multi-granularity modeling is of great significance for improving the reliability, usability, reusability and interoperability of simulation.

In addition, the complex environment of the battlefield—whether it is the natural environment or man-made interference will affect the communication system. For electromagnetic waves, it mainly manifests as the transmission effect of the signal on the propagation path. A typical battlefield environment is mainly divided into natural environment and artificial environment. The natural environment includes factors such as clouds, rain, atmosphere, ionosphere, and terrain, which mainly affect the transmission of electromagnetic signals in the form of noise and attenuation, thereby affecting the communication system; the artificial environment mainly It's electronic interference. The reality and effectiveness of the environment, while not affecting the real-time performance of the entire simulation system, is an important factor in the performance analysis of the communication system.

Due to the advantages of safety, good economy and repeatability, modeling and simulation technology has been widely used in concept demonstration, research and development, training exercises and military operations in the military field. Therefore, research on the multi-granularity modeling of the communication system oriented to confrontation simulation, the impact of the battlefield environment on the military communication system, the performance analysis of the military communication system, etc., and finally the demonstration and verification in typical battlefield scenarios can provide a basis for modern warfare. The military communication system provides an effective simulation process to provide technical support for modern information warfare.

For the application of complex military systems in confrontation simulation, it is necessary to satisfy the real-time and fineness of simulation. For the communication model of the system and countermeasure simulation, the following problems should be solved:

1) The system-level confrontation simulation needs to consider the influence of the electromagnetic environment on the combat of different entities, and also ensure the real-time performance of the simulation;

2) There are some professional-level simulation software for antenna and link simulation. If you want to obtain high-fidelity calculation results, you need to use these software. However, professional software takes a long time and does not have real-time performance. In confrontation simulation, you need The model can run independently of these software, packaged independently as a component and integrated into the equipment model (such as aircraft, armored vehicle) to run in real time;

For the simulation of the communication network, not only the simulation of the entire process of packet transmission is required, but also the real-time excitation characteristics of the equipment during combat and the dynamic influence of the simulation environment should be considered.

Contents of the invention

The present invention aims to provide a real-time simulation method for multi-granularity modeling of a communication system in countermeasure simulation, so as to solve or improve at least one of the above-mentioned technical problems.

In view of this, the first aspect of the present invention is to provide a real-time simulation method for multi-granularity modeling of a communication system in countermeasure simulation.

The first aspect of the present invention provides a real-time simulation method for multi-granularity modeling of the communication system in countermeasure simulation, including: S1, according to the performance index requirements of the antenna design, using electromagnetic simulation software to obtain the off-line power pattern data of the antenna, and then Process the power pattern data into a three-dimensional pattern, and perform online interpolation to obtain online continuous data; S2, build a link calculation simulation model, and establish an engineering-level model and a functional-level model; then use the frequency and bandwidth of the transmitting device , transmit power, and antenna gain. For the calculation of antenna gain, based on the online continuous data, the engineering-level model is obtained by offline calculation in the first step and online interpolation; in the functional-level model, the empirical formula is used to obtain the maximum value of the antenna After the gain, use the inherent parameters of the antenna to calculate the main lobe, half-power beam width, side lobe gain and back lobe gain of the antenna according to the antenna pattern, so as to describe the directivity of the antenna; S3, establish a link calculation simulation model The mission-level model in , which simulates a military communication network, only calculates the coverage of the communication. S4. Establish a model of the impact of a typical battlefield environment on communications, the model including: a battlefield atmospheric environment model, a terrain visibility model, and a jammer model; wherein, the engineering-level model, the function-level model, and the mission-level model The granularity of the model ranges from fine to coarse.

The present invention provides a real-time simulation method for multi-granularity modeling of communication systems in countermeasure simulation. By establishing the battlefield air environment model, terrain visibility model and jammer model respectively, since the propagation of the signal is realized by the propagation of electromagnetic waves, it can affect the Atmospheric absorption loss of electromagnetic wave propagation includes the absorption loss of oxygen and water vapor, terrain height, and active suppression interference factors, and more accurately describes the influence of the electromagnetic environment on the communication system in the system-level countermeasure simulation while ensuring the real-time performance of the simulation ;

The engineering-level model, function-level model and task-level model for military communication network simulation are models with granularity ranging from fine to coarse, and the off-line power pattern data of the antenna is obtained by using electromagnetic simulation software, and then the off-line data is processed into Three-dimensional direction diagram, and online continuous data are obtained by online interpolation, which together form a combination of multi-granularity models. On the whole, it integrates multiple software advantages of multi-granularity communication models, network simulation and electromagnetic environment. Compared with professional electromagnetic simulation software , can be solved online in real time, and compared with network simulation software environment modeling is more detailed, it can better reflect the physical and dynamic characteristics of equipment, and support combat system simulation.

In addition, the technical solutions provided according to the embodiments of the present invention may also have the following additional technical features:

In any of the above technical solutions, the typical battlefield environment includes: a natural environment and an artificial environment, the natural environment includes an atmospheric environment and a terrain environment, and the atmospheric environment includes oxygen and water vapor; the battlefield atmospheric environment model uses It is used to calculate the influence of oxygen and water vapor absorption loss on electromagnetic wave propagation in the battlefield atmospheric environment model; the terrain visibility model is used to calculate the influence of terrain elevation data on electromagnetic wave propagation in the terrain environment; the jammer The model is used to calculate the impact of active suppression interference on communication in the artificial environment.

In this technical solution, the integrated consideration of various environmental factors in the battlefield environment ensures a more comprehensive simulation of the battlefield environment, such as atmospheric absorption loss including the absorption loss of oxygen and water vapor, the absorption effect of tropospheric oxygen on electromagnetic waves, The influence of terrain elevation data on the propagation of electromagnetic waves in the terrain environment. In free space, the environment of the equipment to be interfered is close to ideal, and the sending and receiving signals will not receive any interference. The noise and target echo generated inside the receiver The ratio between the power intensities determines the coverage of the equipment to be interfered. The following factors are considered in the interference: the target echo power intensity, the average power intensity of the receiver thermal noise of the equipment to be interfered with, the signal-to-noise ratio in free space, and the Calculation of the interference power intensity of the receiver of the device to be interfered with under the condition of source suppressed interference, the gain of the antenna of the interfered device in the direction of the jammer, and the signal-to-interference ratio at the output of the receiver under the condition of active suppressed interference.

In any of the above technical solutions, the functional-level model is provided with an output port for at least one of the following functions: obtaining the signal frequency of the transmitting device, obtaining the bandwidth of the transmitting device, obtaining the transmission gain of the transmitting device, and obtaining the frequency of the transmitting device. transmit power, get transmit equipment

The location of the link, the connection result of the link and the bit error rate of the link are obtained; the functional level model is provided with an input port for at least one of the following functions: input model position, input interference power, input required The launch parameters of the receiving device and the attitude angle of the carrier carried by the input device.

In this technical solution, in order to facilitate the subsequent confrontation simulation, a functional-level model with an interface is designed, which enables the modeling method to run independently of these software, and is packaged independently as a component and integrated into the equipment model (aircraft) in real time solve.

In any of the above-mentioned technical solutions, the step of S1 specifically includes: S101, solving the physical field of the antenna, and obtaining the three-dimensional field strength pattern data of the two-dimensional gain pattern of the antenna; S102, calculating and obtaining the referenced ideal each The field strength data of the isotropic antenna, then calculate the absolute gain value of each point, and finally obtain the three-dimensional gain pattern data of the antenna; S103, according to the antenna three-dimensional gain pattern data obtained in the step S102, adopt a bidirectional interpolation algorithm to interpolate, Get the continuous data needed in the simulation process.

In this technical solution, calculations at the physical field level are performed on the antennas of the transmitting and receiving devices, and data processing is performed. According to the performance index requirements of the antenna design, select the appropriate geometric parameters, and use the electromagnetic simulation software to obtain its more accurate and fine power pattern, so as to obtain the gain of the antenna in all directions. After the offline data is obtained, the data is processed into the format of "direction angle-altitude angle-gain" of the three-dimensional pattern, and online interpolation is performed, so as to obtain online continuous data during real-time simulation.

In any of the above technical solutions, the step of S2 specifically includes: S201, establishing an engineering-level model, based on the empirical formula of the maximum gain of a typical aperture antenna, calculating the maximum gain of a typical aperture antenna, and according to the inherent parameters of the antenna and online The antenna pattern of the continuous data, obtain the half-power beam width, side lobe gain and back lobe gain, and describe the directivity of the antenna; S202, calculate the free space loss during the transmission process and include the thermal noise of the system and the typical battlefield environment Variable noise loss; S203, modeling the function-level model, passing the input parameters required by the function-level model to the function-level model at one time through the data input and output parameters, or outputting the function-level model in the current frame to the engine The data is transmitted in the form of a signal; S204, the signal is amplified by the transmitting antenna and propagated, received by the receiving antenna, and the bit error rate of the link is calculated through the signal-to-noise ratio, and the antenna pointing relative to the The azimuth and altitude angles of the ground coordinate system.

In this technical solution, the frequency, bandwidth, transmission power, and antenna gain of the transmitting device are used. For the calculation of the antenna gain, the engineering-level model is obtained by offline calculation in the first step and online interpolation; in the functional-level model, after obtaining the maximum gain of the antenna using the empirical formula, using the inherent parameters of the antenna, according to the typical antenna The pattern calculates the main lobe of the antenna (that is, the maximum gain), the half-power beam width (that is, the angle when the gain is half of the maximum gain), the side lobe gain, and the back lobe gain, thereby depicting the directivity of the antenna.

In any of the above-mentioned technical solutions, the steps of S3 specifically include: S301, setting up a task-level model of the communication system; S302, utilizing ns2 to carry out military communication network simulation; The ns2 can be linked with the model running in the windows environment.

In this technical solution, the task-level model of the communication system is designed and the military communication network simulation is carried out. In order to meet the real-time performance of the military communication network simulation, the task-level model does not consider the directionality for the time being, but only calculates the coverage of the communication. The communication network between different units on the battlefield is mainly represented by the tactical Internet. The tactical Internet generally adopts the AdHoc network. The AdHoc network simulation solution uses the communication network simulation software to calculate the packet loss rate of the entire communication network, the arrival time of the first packet, Latency and other indicators.

In any of the above-mentioned technical solutions, the step of S4 specifically includes: S401, establishing a battlefield atmospheric environment model, establishing a battlefield atmospheric environment model including the variables of oxygen and water vapor absorbing factors of electromagnetic waves; S402, establishing a terrain visibility model , obtaining multiple sampling points of the projection of the line of sight between the viewpoint and the target point on the xoy plane, judging the slope of the line between the viewpoint and the sampling point and the slope of the line of sight and the visibility between the viewpoint and the target point; S403, Establish the jammer model, including the target echo power intensity, the average power intensity of the receiver thermal noise of the equipment to be interfered with, the signal-to-noise ratio in free space, the interference power intensity of the receiver of the equipment to be interfered with under active suppression, and the interference A jammer model of the gain of the device antenna in the direction of the jammer and the variation of the signal-to-interference ratio at the receiver output in the case of active suppressed jamming.

In this technical solution, a model of the influence of typical battlefield environment on communication is established. Typical battlefield environments include natural environment and artificial environment. Natural environment includes atmospheric environment and terrain environment. Atmospheric environment includes oxygen and water vapor absorption models. Terrain environment calculates the influence of terrain elevation data on the visibility of electromagnetic wave propagation. The artificial environment is the jammer model, and the impact of active suppression jamming on communication is calculated.

The present invention has the beneficial effect compared with prior art:

In the system-level confrontation simulation, it is necessary to consider the influence of the electromagnetic environment on the combat of different entities. Most of the existing countermeasure simulation platforms use probability to process communication transmission. The present invention can describe the electromagnetic environment more accurately while ensuring the real-time performance of the simulation The impact of the environment on the communication system in the system-level countermeasure simulation;

For professional electromagnetic simulation software, the solution results with high fidelity can be obtained through these software. At the same time, in order to be applied in the countermeasure simulation scene, the modeling method of the present invention can run independently of these software, and can be independently packaged and distributed as a component. Integrated into the equipment model (aircraft) for real-time calculation;

Existing communication network simulation software does not have enough fidelity to simulate physical characteristics such as antennas, nor can it simulate the dynamic characteristics of equipment during movement. The present invention can effectively integrate multi-granularity models with high fidelity and dynamic characteristics to support combat System simulation.

Additional aspects and advantages of embodiments according to the invention will become apparent in the description which follows, or may be learned by practice of embodiments according to the invention.

Description of drawings

The drawings are only for the purpose of illustrating specific embodiments and are not to be considered as limiting the invention.

Fig. 1 is the overall flowchart of the present invention;

Figure 2 is a typical antenna pattern;

Fig. 3 is the link solution flow chart of the present invention;

Fig. 4 is the communication network emulation process of the present invention;

Fig. 5 is the bilinear interpolation schematic diagram of the present invention;

Fig. 6 is the calculation flow chart of signal-to-noise ratio of the present invention;

Fig. 7 is a schematic diagram of the interface parameters of the function-level model of the present invention.

Detailed ways

In order to have a clearer understanding of the above objects, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

Example 1

The embodiment of the first aspect of the present invention, as shown in FIGS. 1-7 , provides a real-time simulation method based on multi-granularity modeling of a communication system in countermeasure simulation. The example antenna used in this example is an axial mode helical antenna, where the method includes:

Step 1: Calculate the physical field level for the antennas of the transmitting and receiving devices, and perform data processing. According to the performance index requirements of the antenna design, select the appropriate geometric parameters, and use the electromagnetic simulation software to obtain its more accurate and fine power pattern, so as to obtain the gain of the antenna in all directions. After the offline data is obtained, the data is processed into the format of "direction angle-altitude angle-gain" of the three-dimensional pattern, and online interpolation is performed, so as to obtain online continuous data during real-time simulation.

Step 101: First, calculate the physical field of the antenna. Using AntennaMagus software, taking the axial mode helical antenna as an example, the proposed design performance index requirements are shown in Table 1:

Table 1 Requirements for Design Performance Index of Axial Mode Helical Antenna

Operating frequency f₀ absolute gain Material diameter D_w 1GHz 10dBi 3mm

Then the geometric parameters of the axial mode helical antenna are designed, and the geometric parameters are shown in Table 2:

Table 2 Geometric parameters of axial mode helical antenna

D_w 3mm D_g 299.8mm Dh 95.43mm h Right-handed H_f 11.99mm N 4 φ 13°

Get the three-dimensional field strength pattern data of the two-dimensional gain pattern of the antenna, and the data are shown in Table 3 and Table 4:

Table 3 Partial data of antenna two-dimensional gain pattern

Table 4 Partial data of antenna three-dimensional field strength pattern

Theta Phi Re(E_Theta Im(E_Theta) Re(E_Phi) Im(E_Phi) 0.00E+00 0.00E+00 5.11E+00 2.03E+00 1.58E-02 9.04E-02 1.00E+00 0.00E+00 5.04E+00 2.33E+00 1.57E-02 9.01E-02 3.00E+00 0.00E+00 4.95E+00 2.63E+00 1.56E-02 8.97E-02 4.00E+00 0.00E+00 4.85E+00 2.92E+00 1.55E-02 8.94E-02 5.00E+00 0.00E+00 4.73E+00 3.20E+00 1.54E-02 8.91E-02 6.00E+00 0.00E+00 4.60E+00 3.47E+00 1.46E-02 8.88E-02

Step 102: For subsequent data applications, it is expected to obtain a three-dimensional gain pattern of the antenna. The definition of gain refers to the ratio of the radiation intensity of the antenna to the ideal isotropic antenna. Therefore, if you want to calculate the field data of the antenna gain, you need to calculate the field strength data of the ideal isotropic antenna referenced, and then calculate the no-point The absolute gain value is finally obtained to obtain the three-dimensional gain pattern data of the antenna.

Step 103: The obtained antenna three-dimensional gain pattern data is discrete data, but continuous data is required in the simulation process, so the data needs to be interpolated. A bidirectional interpolation algorithm is used for interpolation. The schematic diagram of bilinear interpolation is shown in Figure 5. The calculation results of interpolation are as follows:

Some results of interpolation are shown in Table 5:

Table 5 Partial interpolation results

Step 2: Construct link calculation simulation model, and establish engineering-level and functional-level models of the communication system. The process is shown in Figure 2. Frequency, bandwidth, transmit power, and antenna gain of the transmitting device. For the calculation of antenna gain, the engineering-level model is obtained by offline calculation in the first step and online interpolation; in the functional-level model, after the maximum gain of the antenna is obtained by using the empirical formula, the inherent parameters of the antenna are used, according to Figure 3 The typical antenna pattern shown calculates the antenna's main lobe (i.e., maximum gain), half-power beamwidth (i.e., the angle at which the gain is half the maximum gain), sidelobe gain, and backlobe gain, thereby depicting the antenna's directivity .

Step 201: In order to calculate the maximum gain of a typical aperture antenna, the empirical formula of the maximum gain of some typical aperture antennas is obtained by consulting the data, as shown in Table 6:

Empirical formulas for the maximum gain of typical aperture antennas in Table 5

After obtaining the maximum gain of the antenna, use the inherent parameters of the antenna to calculate the main lobe of the antenna, which is the maximum gain, according to the typical antenna pattern shown in Figure 3, and the half-power beam width is the angle when the gain is half of the maximum gain. The lobe gain and the back lobe gain, thus depicting the directivity of the antenna.

Step 202: Calculate the free space loss in the transmission process, the signal-to-noise ratio with only free space loss is as follows:

In addition to the free space loss in the above formula, noise loss is also introduced. In addition to the thermal noise of the system itself, the noise is mainly affected by the battlefield environment. The modeling of this part will be introduced in the fourth step. Then, the process shown in FIG. 6 calculates the signal-to-noise ratio of the link.

The bit error rate is an important indicator of the communication performance of the communication system, and the bit error rate is defined as:

Through the signal-to-noise ratio, the bit error rate of communication can be calculated according to the following formula:

Through the size of the bit error rate, it can be judged whether communication can be realized, and the range covered by the communication equipment can be calculated in reverse, which provides the basis for the performance evaluation of the communication system.

Step 203: Modeling of the communication system link functional level model, the first is the description of the data type, as shown in Table 6:

Table 6 Introduction of data types of communication system link functional level model

data type name Data Type Description UDPosition Where the model is located Comm_tran The information of the device to be received by the communication device carrier Attitude angle of the carrier device Fixed_para Fixed parameters of the communication device Atmosphere Atmospheric Absorption Factor for Electromagnetic Waves relative_POS The relative position of the receiver relative to the transmitter

In order to facilitate the subsequent confrontation simulation, the above data types are designed. Then introduce the parameters of the model. The parameters of the model include initialization parameters and input parameters. The main function of the initialization parameters is to initialize the model and set the model initialization parameters. The parameters of the initialization setting only need to be set once, and do not need to be set every time the calculation is performed.

Pass all or part of the input parameters required by the model to the model entity at one time through the data input and output parameters. Similarly, the data output interface passes the data that the entity in the current frame needs to output to the engine at one time through the same data structure. The interface of the model is shown in Figure 7:

Step 204: The transmitted signal passes through, amplified by the transmitting antenna, and noise is introduced during propagation, including transmission loss (free space loss, atmospheric transmission loss), system thermal noise, and external interference, and then received by the receiving antenna. The bit error rate of the link can be calculated through the signal-to-noise ratio.

Since communication equipment is usually carried on other carriers such as aircraft and armored vehicles, the direction angle and altitude angle of the above-mentioned antenna pointing are relative to the body coordinate system, and in the process of link calculation, it is necessary to The solution is performed under the system, so coordinate conversion is required. The conversion equation from the ground coordinate system S_g to the body coordinate system S_b is as follows

Assuming that it coincides with the body axis, the height angle and direction angle of the antenna pointing are both 0, and the antenna is regarded as a rigid body, then the coordinates of a certain point of the antenna in the body coordinate system are as follows:

Convert it to coordinates in the ground coordinate system:

The azimuth and elevation angles of the antenna pointing relative to the ground coordinate system are then obtained:

The third step: design the task-level model of the communication system, and carry out military communication network simulation. The process of military communication network simulation is shown in Figure 4. In order to meet the real-time performance of military communication network simulation, the task-level model does not consider the directionality for the time being, and only calculates the coverage of the communication. The communication network between different units on the battlefield is mainly represented by the tactical Internet. The tactical Internet generally adopts the AdHoc network. The AdHoc network simulation solution uses the communication network simulation software to calculate the packet loss rate of the entire communication network, the arrival time of the first packet, Delay time and other indicators, the communication network simulation process is shown in Figure 4.

Step 301: Establish a task-level model of the communication system. In order to meet the real-time performance of the communication network simulation during the countermeasure simulation, the directionality of the communication equipment is not considered, only the fixed antenna gain of the facility is required, and only the coverage of the equipment is considered.

Step 302: The flow of communication network modeling and simulation using ns2 is shown in Figure 4. First, set the simulation scene through the TCL script. The TCL script can set the interface to receive external input data, and can receive simulation scenario data, such as the location of the node. Information, etc., and then set the step size, each time as a simulation step length, and then analyze the obtained tr file to analyze the effect of the tactical Internet. The transmission model of ns2 is relatively coarse, so the loss model of ns2 and the antenna model can be modified, and thus establish links with other granular models that have been established. The specific meanings of the parameters of the wireless communication network are shown in Table 7:

Table 7 The specific meaning of the parameters of the wireless communication network

When setting the node position in the TCL script, this can be written in a form that can receive external input in real time. In addition to this, the antenna gain can also receive the input of an externally established model instead of manual setting, and because the antenna gain can only be set once. , cannot be set separately for each node, so an average value of the entire network gain can be received here.

After running the simulation scenario, you can save the results to a tr file. The meaning of each column in the tr file is shown in Table 8:

Calculate the packet loss rate of the entire communication network, the arrival time of the first packet, and the delay time by analyzing the tr file.

Step 303: Because ns2 needs to run in the linux environment, in order to connect with the model running in the windows environment, socket communication is required. First, set the simulation step size, where the CBR start and end time can be set as the simulation step size through external input, for example, 0.2s. Then every 0.2s of the simulation time, the external model transmits information such as the position of the node at this time to the linux environment through the socket, and the tcl file controls ns2 to perform 0.2s simulation. The combat simulation program running on Windows is used as the client program Client, and the program that calls ns2 for tactical Internet simulation running under the Linux environment is used as the server program Server. The Client will need to transmit information to the tcl script to control the ns2 simulation every other simulation step Pass it to the server side. After the server receives the information, it creates a sub-process, calls the system function system(ns***.tcl), and starts a ns2 simulation with a simulation step. Each simulation stores the simulation results in the tr file,

Step 4: Model the impact of a typical battlefield environment on communications. Typical battlefield environments include natural environment and artificial environment. Natural environment includes atmospheric environment and terrain environment. Atmospheric environment includes oxygen and water vapor absorption models. Terrain environment calculates the influence of terrain elevation data on the visibility of electromagnetic wave propagation. The artificial environment is the jammer model, and the impact of active suppression jamming on communication is calculated.

Step 401: First establish an atmospheric environment model of the battlefield. Atmospheric absorption loss includes the absorption loss of oxygen and water vapor. According to the American Standard Atmospheric Model, the relationship between tropospheric atmospheric pressure P, temperature T, water vapor density ρ and height h is as follows:

In the formula, α=52561222, β=0.034164794, R_0 is the radius of the earth (m), h is the height (m), T is the temperature (K), and the water vapor density in the troposphere is as follows:

In the formula, h is the height, and _ci is a constant, which can be obtained by consulting relevant literature.

In addition to the tropospheric atmospheric model, there is also the absorption effect of tropospheric oxygen on electromagnetic waves, so it is necessary to establish an oxygen absorption factor model. The absorption of tropospheric oxygen for electromagnetic waves is the sum of many resonance spectral lines around 60 GHz. The expression of the absorption factor of oxygen for an electromagnetic wave of any frequency f is as follows:

In the formula, A _N is the summation term of each resonance number N.

The summation term of each resonance number N is as follows:

In the formula,

Tropospheric water vapor absorption is divided into two parts: the resonance at 22.235 GHz with an absorption factor of ξ_22(h) and the side effects of some resonant spectral lines above 100 GHz with an absorption factor of ξ_res(h)

F为频率效应。In the formula,

F is the frequency effect.

Atmospheric absorption loss model can be linked with engineering-level and functional-level models in the form of noise loss. In addition, it can also be added to ns2 transmission model and recompiled to make ns2 transmission loss more accurate.

Step 402: Establish a terrain visibility model. Treat the earth as a plane. After determining the viewpoint and target point in the plane geodetic coordinate system, project the line of sight on the xoy plane, and obtain several sampling points uniformly on the projection line, and query the DEM data to obtain the elevation of each sampling point. , to judge the visibility between the viewpoint and the target point.

Take a number of sampling points between the viewpoint and the target point, starting from sampling point 1, if the slope of the line connecting the viewpoint and the sampling point is smaller than the slope of the line of sight, it means that the current sampling point does not affect the visibility, and advance to the next sampling point to continue Compare slopes;

If the slope of the line connecting the viewpoint and a certain sampling point is greater than the slope of the line of sight, the viewpoint and the target point cannot be seen through, and the calculation ends. If you can advance all the way to the target point, it means that the view point and the target point can communicate with each other.

Step 403: Establish a jammer model. In free space, the environment of the device to be interfered is close to ideal, and the sending and receiving signals will not receive any interference, and the coverage of the device to be interfered is determined by the ratio between the noise generated inside the receiver and the target echo power intensity scope. Among them, the target echo power intensity is as follows:

In the formula, P _t is the transmitting power, G _t is the gain of the transmitting antenna, G _r is the gain of the receiving antenna, λ is the wavelength, and R is the distance.

The average power intensity of the receiver thermal noise of the equipment to be interfered is as follows:

N=kT ₀ B _r F

The signal-to-noise ratio in free space is:

In the formula, K is the Boltzmann constant, T ₀ is the receiver noise temperature, B _r is the receiver bandwidth, and F is the receiver noise figure.

Under active suppression interference, the interference power intensity of the receiver of the device to be interfered is:

The gain of the jamming device antenna in the direction of the jammer is:

In the formula, θ _0. is the main board gain of the receiver antenna, θ is the angle between the connection between the transmitter and the receiver and the connection between the receiver of the jammer, K is a constant, and the value is determined according to the performance parameters of the receiver.

In the case of active suppression of interference, the signal-to-interference ratio at the output of the receiver is calculated as follows:

In the formula, P _x is the signal power received by the receiver.

The established jammer parameters are shown in Table 9:

Table 9 Jammer parameters

In describing the present invention, it should be understood that the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", The orientations or positional relationships indicated by "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention, rather than indicating or It should not be construed as limiting the invention by implying that a referenced device or element must have a particular orientation, be constructed, and operate in a particular orientation.

The above-mentioned embodiments are only to describe the preferred mode of the present invention, not to limit the scope of the present invention. Without departing from the design spirit of the present invention, those skilled in the art may make various Variations and improvements should fall within the scope of protection defined by the claims of the present invention.

Claims (7)

1. A communication system multi-granularity modeling real-time simulation method in countermeasure simulation, it is characterized in that, comprising: S1, according to the performance index requirements of the antenna design, use electromagnetic simulation software to obtain the offline power pattern data of the antenna, then process the power pattern data into a three-dimensional pattern, and perform online interpolation to obtain online continuous data; S2. Construct a link calculation simulation model, and establish an engineering-level model and a functional-level model; then use the frequency, bandwidth, transmission power, and antenna gain of the transmitting device. The calculation of the antenna gain is based on online continuous data through engineering The model at the first step is obtained by offline calculation and online interpolation; in the model at the functional level, after the maximum gain of the antenna is obtained by using the empirical formula, the main lobe of the antenna is calculated according to the antenna pattern by using the inherent parameters of the antenna. Power beamwidth, sidelobe gain and backlobe gain, thus depicting the directivity of the antenna; S3, establish a task-level model in the link calculation simulation model, perform military communication network simulation, and only calculate the coverage of communication; S4, establishing a model of the impact of a typical battlefield environment on communication, said model including: a battlefield atmospheric environment model, a terrain visibility model, and a jammer model; Wherein, the granularity of the engineering level model, the function level model and the task level model ranges from fine to coarse. 2. the communication system multi-granularity modeling real-time simulation method in a kind of confrontation simulation according to claim 1, is characterized in that, described typical battlefield environment comprises: natural environment and artificial environment, and described natural environment comprises atmospheric environment and Terrain environment, said atmospheric environment includes oxygen and water vapour; The battlefield atmospheric environment model is used to calculate the influence of oxygen and water vapor absorption loss on electromagnetic wave propagation in the battlefield atmospheric environment model; The terrain visibility model is used to calculate the influence of terrain elevation data on electromagnetic wave propagation in the terrain environment; The jammer model is used to calculate the impact of active suppression jamming on communication in the artificial environment. 3. the communication system multi-granularity modeling real-time simulation method in a kind of confrontation simulation according to claim 1, it is characterized in that, described function level model is provided with output port, is used to realize at least one of following functions: get launch The signal frequency of the device, the bandwidth of the transmitting device, the transmitting gain of the transmitting device, the transmitting power of the transmitting device, the location of the transmitting device, the connection result of the link and the bit error rate of the link; The function-level model is provided with an input port for realizing at least one of the following functions: inputting the position of the model, inputting the interference power, inputting the transmission parameters of the receiving device and inputting the attitude angle of the carrier carried by the device. 4. The real-time simulation method for multi-granularity modeling of a communication system in a countermeasure simulation according to claim 1, wherein the step of S1 specifically includes: S101, performing antenna physical field calculation to obtain three-dimensional field strength pattern data of the two-dimensional gain pattern of the antenna; S102, calculate the field strength data of the referenced ideal isotropic antenna, then calculate the absolute gain value of each point, and finally obtain the three-dimensional gain pattern data of the antenna; S103, according to the three-dimensional gain pattern data of the antenna obtained in step S102, interpolation is performed by adopting a bidirectional interpolation algorithm to obtain continuous data required in the simulation process. 5. The real-time simulation method for multi-granularity modeling of a communication system in a countermeasure simulation according to claim 1, wherein the step of S2 specifically includes: S201, based on the empirical formula of the maximum gain of a typical aperture antenna, calculate the maximum gain of a typical aperture antenna, and obtain the half-power beam width, side lobe gain and back lobe gain according to the inherent parameters of the antenna and the antenna pattern of the online continuous data , depicting the directivity of the antenna; S202, calculating free space loss during transmission and noise loss including variables of system thermal noise and typical battlefield environment; S203, modeling the function-level model, passing the input parameters required by the function-level model to the function-level model at one time through data input and output parameters, or sending the data that the function-level model needs to output to the engine in the current frame in the form of a signal pass it on; S204, the signal is propagated after being amplified by the transmitting antenna, received by the receiving antenna, the bit error rate of the link is calculated through the signal-to-noise ratio, and the direction angle and height of the antenna pointing relative to the ground coordinate system are obtained by coordinate conversion based on the directivity of the antenna horn. 6. The real-time simulation method for multi-granularity modeling of a communication system in a countermeasure simulation according to claim 1, wherein the step of S3 specifically includes: S301, establishing a task-level model of the communication system; S302, use ns2 to simulate military communication network; S303, performing socket communication, so that the ns2 running in the linux environment can be connected with the model running in the windows environment. 7. The real-time simulation method for multi-granularity modeling of a communication system in a countermeasure simulation according to claim 6, wherein the step of S4 specifically includes: S401, establishing a battlefield atmospheric environment model, establishing a battlefield atmospheric environment model including variables of oxygen and water vapor absorption factors for electromagnetic waves; S402, establish a terrain visibility model, obtain multiple sampling points of the projection of the line of sight between the viewpoint and the target point on the xoy plane, determine the slope of the line connecting the viewpoint and the sampling point and the slope of the line of sight, and the distance between the viewpoint and the target point Visibility between S403, establish a jammer model, including the target echo power intensity, the average power intensity of thermal noise of the receiver of the equipment to be interfered with, the signal-to-noise ratio in free space, and the interference power intensity of the receiver of the equipment to be interfered with under active interference suppression , the gain of the jammer's antenna in the direction of the jammer and the jammer model of the variable of the signal-to-interference ratio at the output of the receiver in the case of active suppression of jamming.

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