CN115270590A - Multi-granularity modeling real-time simulation method for communication system in countermeasure simulation - Google Patents
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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
Technical Field
The invention relates to the technical field of multi-granularity modeling of combat simulation and battlefield communication systems, in particular to a multi-granularity modeling real-time simulation method of a communication system in countermeasure simulation.
Background
The historical development of wars is closely related to the development of military communication systems, and the wars evolve from original communication systems such as the earliest demi-wolf alarms to the military communication systems of today. With the development of science and technology, informatization has become one of the important indexes of military combat effectiveness today, and modeling and simulation of a communication system facing countermeasure simulation are important research directions for evaluating informatization of military.
A communication system is a very complex system, and how to accurately model the system and meet the requirement of real-time performance is a problem worthy of research. The establishment of models with different granularities for description and analysis is a very effective means for processing complex problems, and can effectively solve the problems of the fineness degree and the simulation real-time property of the models. For modeling and simulation of the communication system, the contradiction between the fineness of the model and the simulation real-time performance can be solved by adopting a multi-granularity modeling mode, so that the multi-granularity modeling of the communication system is necessary to be researched.
Multi-granularity modeling has become a research hotspot in the field of modeling and simulation. Although there are many problems to be solved in theory and technology, the importance of the multi-granularity modeling technology in distributed simulation has been shown. The development of multi-granularity modeling research has important significance for improving the credibility, the availability, the reusability and the interoperability of simulation.
In addition, the complex environment of the battlefield, whether natural or man-made interference, affects the communication system, and for electromagnetic waves, it is mainly manifested as the transmission effect of signals on the propagation path. Typical battlefield environments are mainly divided into natural environments and artificial environments, wherein the natural environments comprise factors such as cloud, rainfall, atmosphere, ionized layer and terrain, and mainly influence the transmission of electromagnetic signals in a noise and attenuation manner so as to influence a communication system; the artificial environment is mainly electronic interference. The reality and effectiveness of the environment cannot influence the real-time performance of the whole simulation system, and the real-time performance cannot influence the real-time performance of the whole simulation system.
Because of the advantages of good safety and economy, repeatability and the like, the modeling and simulation technology is widely applied to concept demonstration, research and development, training and exercise in the military field and military operations nowadays. Therefore, the method researches the multi-granularity modeling of the communication system for the countermeasure simulation, the influence of the battlefield environment on the military communication system, the performance analysis of the military communication system and the like, and finally performs the demonstration and verification under a typical battlefield scene, thereby providing an effective simulation process for the military communication system of the modern war and providing technical support for the modern informatization combat.
Aiming at the application of a complex military system in countermeasure simulation, the real-time performance and the fineness degree of the simulation are considered. For the communication model of architecture and counter simulation, the following problems should be solved:
1) The system-level confrontation simulation needs to consider the influence of electromagnetic environment on the battle of different entities and ensure the real-time performance of the simulation;
2) Antenna and link simulation are provided with some professional-level simulation software, if a calculation result with higher fidelity is obtained, the software needs to be used, but the professional software is long in time consumption and has no real-time performance, and in countermeasure simulation, a model is required to be capable of running independently of the software and to be independently packaged as a component and integrated into an equipment model (such as an airplane and an armored car) to run in real time;
for the simulation of the communication network, not only the simulation of the whole flow of the packet transmission is required, but also the real-time activation characteristic of the equipment during the battle and the dynamic influence of the simulation environment are considered.
Disclosure of Invention
The present invention is directed to a multi-granularity modeling real-time simulation method for a communication system in a countermeasure simulation, so as to solve or improve at least one of the above technical problems.
In view of the above, a first aspect of the present invention is to provide a multi-granularity modeling real-time simulation method for a communication system in a countermeasure simulation.
The invention provides a multi-granularity modeling real-time simulation method for a communication system in countermeasure simulation, which comprises the following steps: s1, according to the performance index requirement of antenna design, obtaining offline power directional diagram data of an antenna by using electromagnetic simulation software, processing the power directional diagram data into a three-dimensional directional diagram, and performing online interpolation to obtain online continuous data; s2, constructing a link calculation simulation model, and establishing an engineering-level model and a functional-level model; then, the calculation of the antenna gain is obtained by an engineering-level model based on online continuous data in a mode of off-line calculation in the first step and online interpolation through the frequency, the bandwidth, the transmitting power and the antenna gain of transmitting equipment; after the maximum gain of the antenna is obtained by adopting an empirical formula in the functional level model, the main lobe, the half-power beam width, the side lobe gain and the back lobe gain of the antenna are calculated according to an antenna directional diagram by utilizing the inherent parameters of the antenna, so that the directivity of the antenna is described; and S3, establishing a task-level model in the link calculation simulation model, performing military communication network simulation, and only calculating the coverage of communication. S4, establishing a model of the influence of a typical battlefield environment on communication, wherein the model comprises the following steps: a battlefield atmospheric environment model, a terrain visibility model and an interference machine model; wherein the granularity of the engineering-level model, the functional-level model and the task-level model is from fine to coarse.
The invention provides a multi-granularity modeling real-time simulation method of a communication system in countermeasure simulation, which comprises the steps of respectively establishing a battlefield gas environment model, a terrain visibility model and an interference machine model, and considering atmospheric absorption loss including absorption loss of oxygen and water vapor, terrain height and active suppression interference factors which can influence electromagnetic wave transmission because the transmission of signals is realized through the transmission of electromagnetic waves, so that the influence of an electromagnetic environment on the communication system in system-level countermeasure simulation is more accurately described while the real-time performance of the simulation is ensured;
the engineering-level model, the functional-level model and the task-level model for military communication network simulation are models with the granularity from fine to coarse, offline power directional diagram data of an antenna are obtained by utilizing electromagnetic simulation software, then the offline data are processed into a three-dimensional directional diagram, online continuous data are obtained by online interpolation, and a combination of multi-granularity models is formed together.
In addition, the technical solution provided by the embodiment of the present invention may further have the following additional technical features:
in any of the above solutions, the typical battlefield environment includes: the natural environment comprises an atmospheric environment and a topographic environment, and the atmospheric environment comprises oxygen and water vapor; the battlefield atmospheric environment model is used for calculating the influence of the absorption loss of oxygen and water vapor in the battlefield atmospheric environment model on the electromagnetic wave propagation; the terrain visibility model is used for calculating the influence of terrain elevation data in the terrain environment on electromagnetic wave propagation; the interference machine model is used for calculating the influence of active suppression interference on communication in the artificial environment.
In the technical scheme, by integrally considering various environmental factors in a battlefield environment, the simulation of the battlefield environment is more comprehensive, for example, atmospheric absorption loss comprises absorption loss of oxygen and water vapor, absorption effect of tropospheric oxygen on electromagnetic waves, influence of topographic elevation data in a topographic environment on electromagnetic wave propagation, in a free space, the environment where equipment to be interfered is located is close to idealization, signals sent and received cannot receive any interference, the coverage range of the equipment to be interfered is determined by the ratio between noise generated inside a receiver and target echo power intensity, and the following factors are considered in the interference: the method comprises the following steps of target echo power strength, average power strength of thermal noise of a receiver of a device to be interfered, signal-to-noise ratio in free space, interference power strength of the receiver of the device to be interfered under active interference suppression, gain of an antenna of the interfering device in the direction of an interference machine and signal-to-interference ratio calculation of an output end of the receiver under the active interference suppression.
In any of the above technical solutions, the function level model is provided with an output port for at least one of the following functions: obtaining the signal frequency of the transmitting equipment, obtaining the bandwidth of the transmitting equipment, obtaining the transmitting gain of the transmitting equipment, obtaining the transmitting power of the transmitting equipment and obtaining the transmitting equipment
Obtaining a link communication result and obtaining a link error rate; the function-level model is provided with an input for at least one of the following functions: inputting the position of a model, inputting the interference power, inputting the transmission parameters of the equipment to be received and inputting the attitude angle of a carrier carried by the equipment.
In the technical scheme, in order to facilitate subsequent countermeasure simulation, a functional level model with an interface is designed, so that the modeling method can be operated independently of software, independently packaged as a component and integrated into an equipment model (airplane) for real-time calculation.
In any of the above technical solutions, the step of S1 specifically includes: s101, resolving an antenna physical field to obtain three-dimensional field intensity directional diagram data of an antenna two-dimensional gain directional diagram; s102, calculating field intensity data of the referenced ideal isotropic antenna, then calculating an absolute gain value of each point, and finally obtaining three-dimensional gain directional diagram data of the antenna; and S103, interpolating by adopting a bidirectional interpolation algorithm according to the antenna three-dimensional gain directional diagram data obtained in the step S102 to obtain continuous data required in the simulation process.
In the technical scheme, the antenna of the transmitting and receiving equipment is subjected to physical field level calculation and data processing. According to the performance index requirement of antenna design, selecting proper geometric parameters, and obtaining a more accurate and fine power directional diagram of the antenna by utilizing electromagnetic simulation software, thereby obtaining the gain of the antenna in each direction. After the off-line data is obtained, the data is processed into a 'direction angle-altitude angle-gain' format of a three-dimensional directional diagram, and online interpolation is carried out, so that online continuous data is obtained during real-time simulation.
In any of the above technical solutions, the step of S2 specifically includes: s201, establishing an engineering-level model, calculating the maximum gain of the typical aperture antenna based on an empirical formula of the maximum gain of the typical aperture antenna, obtaining the half-power beam width, the side lobe gain and the back lobe gain according to the inherent parameters of the antenna and the antenna directional diagram of online continuous data, and describing the directivity of the antenna; s202, calculating free space loss in the transmission process and noise loss including system thermal noise and variables of a typical battlefield environment; s203, modeling the function level model, and transmitting 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 transmitting the data required by the function level model in the current frame to the engine in a signal mode; s204, the signal is transmitted after being amplified by the transmitting antenna and received by the receiving antenna, the error rate of the link is calculated through the signal-to-noise ratio, and the direction angle and the altitude angle of the antenna pointing direction relative to a ground coordinate system are obtained through coordinate conversion based on the directivity of the antenna.
In the technical scheme, the frequency, the bandwidth, the transmission power and the antenna gain of the transmitting equipment are used. For the calculation of the antenna gain, an engineering-level model is obtained by utilizing the modes of off-line calculation and on-line interpolation in the first step; after the maximum gain of the antenna is obtained by adopting an empirical formula in the functional level model, the main lobe (namely the maximum gain), the half-power beam width (namely the angle when the gain is half of the maximum gain), the side lobe gain and the back lobe gain of the antenna are calculated according to a typical antenna directional diagram by using the inherent parameters of the antenna, so that the directivity of the antenna is described.
In any of the above technical solutions, the step S3 specifically includes: s301, establishing a task-level model of the communication system; s302, performing military communication network simulation by using ns 2; s303, carrying out socket communication, so that ns2 running in a linux environment can be connected with a model running in a windows environment.
In the technical scheme, a mission-level model of a communication system is designed to carry out military communication network simulation, and in order to meet the real-time performance of the military communication network simulation, the mission-level model temporarily does not consider directionality and only calculates the coverage range of communication. The communication network between different units on a battlefield is mainly represented as a tactical internet which generally adopts an ad hoc network, and the ad hoc network simulation calculation calculates indexes such as packet loss rate, first packet arrival time, delay time and the like of the whole communication network by means of communication network simulation software.
In any of the above technical solutions, the step of S4 specifically includes: s401, establishing a battlefield air environment model, and establishing a battlefield atmospheric environment model comprising variables of absorption factors of oxygen and water vapor on electromagnetic waves; s402, establishing a terrain visibility model, acquiring a plurality of sampling points of the projection of the sight between the viewpoint and the target point on the xoy plane, and judging the size of the slope of the connecting line of the viewpoint and the sampling points and the slope of the sight and the visibility between the viewpoint and the target point; s403, establishing an interference machine model, wherein the interference machine model comprises target echo power intensity, average thermal noise power intensity of a receiver of the device to be interfered, signal-to-noise ratio in free space, interference power intensity of the receiver of the device to be interfered under active suppression interference, gain of an antenna of the interference device in the direction of the interference machine, and variables of signal-to-interference ratio of an output end of the receiver under the active suppression interference.
In the technical scheme, a model of the influence of a typical battlefield environment on communication is established. Typical battlefield environments include natural environments and artificial environments, the natural environments include atmospheric environments and topographic environments, the atmospheric environments include oxygen and water vapor absorption models, and the topographic environments calculate the influence of topographic elevation data on electromagnetic wave propagation visibility. The artificial environment is an interference machine model, and the influence of active suppression interference on communication is calculated.
Compared with the prior art, the invention has the following beneficial effects:
in the system-level countermeasure simulation, the influence of the electromagnetic environment on the battles of different entities needs to be considered, most of communication transmission in the existing countermeasure simulation platform is processed by adopting probability, and the invention can more accurately describe 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;
for professional electromagnetic simulation software, a calculation result with higher fidelity can be obtained through the software, and meanwhile, in order to be applied to a countermeasure simulation scene, the modeling method can be operated independently of the software, is independently packaged as a component and is integrated into an equipment model (airplane) for real-time calculation;
the existing communication network simulation software has insufficient fidelity for physical characteristic simulation of antennas and the like, and cannot simulate dynamic characteristics of equipment during movement.
Additional aspects and advantages of embodiments in accordance with the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of embodiments in accordance with the invention.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention.
FIG. 1 is an overall flow diagram of the present invention;
FIG. 2 is a typical antenna pattern;
FIG. 3 is a link resolution flow diagram of the present invention;
FIG. 4 is a communication network simulation flow of the present invention;
FIG. 5 is a schematic diagram of bilinear interpolation according to the present invention;
FIG. 6 is a flow chart of the signal-to-noise ratio calculation of the present invention;
FIG. 7 is a diagram illustrating interface parameters of a functional level model according to the present invention.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Example 1
Embodiments of the first aspect of the present invention, as shown in fig. 1 to 7, provide a real-time simulation method based on multi-granularity modeling of a communication system in a countermeasure simulation. An example antenna used in this example is an axial mode helical antenna, wherein the method comprises:
the first step is as follows: and resolving the antenna of the transmitting and receiving equipment at the physical field level, and processing data. According to the performance index requirement of antenna design, selecting proper geometric parameters, and obtaining a more accurate and fine power directional diagram of the antenna by utilizing electromagnetic simulation software, thereby obtaining the gain of the antenna in each direction. After the off-line data is obtained, the data is processed into a 'direction angle-altitude angle-gain' format of a three-dimensional directional diagram, and online interpolation is carried out, so that online continuous data is obtained during real-time simulation.
Step 101: firstly, the antenna physical field is resolved, and by using antenna maps software and taking an axial mode helical antenna as an example, the proposed design performance index requirements are shown in table 1:
TABLE 1 axial mode helical antenna design Performance index requirements
| Operating frequency f 0 | Absolute gain | Diameter D of the material w |
| 1GHz | 10dBi | 3mm |
Then, the geometric parameters of the axial mode helical antenna are designed, and are shown in table 2:
TABLE 2 axial mode helical antenna geometry
| D w | 3mm |
| D g | 299.8mm |
| Dh | 95.43mm |
| h | Right hand rotation |
| H f | 11.99mm |
| N | 4 |
| φ | 13° |
Obtaining three-dimensional field intensity directional diagram data of the antenna two-dimensional gain directional diagram, wherein the data are shown in table 3 and table 4:
TABLE 3 antenna two-dimensional gain Pattern part data
TABLE 4 partial data of three-dimensional field intensity pattern of antenna
| 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 desirable to obtain a three-dimensional gain pattern for the antenna. The definition of the gain refers to the ratio of the radiation intensity of the antenna to the ideal isotropic antenna, so that the field data of the antenna gain needs to be calculated to obtain the field intensity data of the referenced ideal isotropic antenna, then the absolute gain value of no point is calculated, and finally the three-dimensional gain directional diagram data of the antenna is obtained.
Step 103: the obtained antenna three-dimensional gain directional diagram data is discrete data, and continuous data is needed in the simulation process, so that interpolation processing needs to be carried out on the data. An interpolation is performed by adopting a bidirectional interpolation algorithm, a schematic diagram of bilinear interpolation is shown in fig. 5, and the calculation result of interpolation is as follows:
partial results of the interpolation are shown in table 5:
table 5 partial interpolation results
The second step: a link solution simulation model is constructed, and engineering-level and functional-level models of the communication system are established, and the flow is shown in fig. 2. By the frequency, bandwidth, transmit power, antenna gain of the transmitting device. For the calculation of the antenna gain, an engineering-level model is obtained by utilizing the modes of off-line calculation and on-line interpolation in the first step; in the functional level model, after the maximum gain of the antenna is obtained by an empirical formula, the main lobe (i.e., the maximum gain), the half-power beam width (i.e., the angle at which the gain is half the maximum gain), the side lobe gain and the back lobe gain of the antenna are calculated according to the typical antenna pattern shown in fig. 3 by using the inherent parameters of the antenna, so as to describe the directivity of the antenna.
Step 201: in order to calculate the maximum gain of the typical aperture antenna, the empirical formula for obtaining the maximum gain of part of the typical aperture antenna by referring to the data is shown in table 6:
TABLE 5 empirical formula for maximum gain of typical aperture antenna
After obtaining the maximum gain of the antenna, the angle at which the main lobe of the antenna, i.e., the maximum gain, the gain, i.e., the half-power beam width, is half the maximum gain, the side lobe gain, and the back lobe gain are calculated from the typical antenna pattern as shown in fig. 3 using the intrinsic parameters of the antenna, thereby describing the directivity of the antenna.
Step 202: the free space loss during transmission is calculated, and the signal-to-noise ratio of the free space loss is as follows:
in addition to the free space loss in the above equation, noise loss is also introduced, wherein the noise is mainly influenced by the battlefield environment in addition to the thermal noise of the system itself, and the modeling of this part will be described in the fourth step. The signal-to-noise ratio of the link is then calculated as in the flow shown in fig. 6.
The bit error rate is an important index of communication performance of a communication system, and is defined as follows:
the bit error rate of the communication can be calculated by the signal-to-noise ratio according to the following formula:
and judging whether the communication can be realized or not according to the error rate, and reversely calculating the range which can be covered by the communication equipment according to the error rate, thereby providing a basis for the performance evaluation of the communication system.
Step 203: modeling of the functional level model of the communication system link, first a description of the data type, as shown in table 6:
table 6 data type introduction of communication system link function level model
| Data type name | Description of data types |
| UDPosition | The position of the model |
| Comm_tran | Information of equipment to be received by communication equipment |
| carrier | Attitude angle of carrier device |
| Fixed_para | Fixed parameters for communication devices |
| Atmosphere | Factor for absorbing electromagnetic wave by atmosphere |
| relative_POS | Relative position of receiver with respect to transmitter |
The above data types are designed for the convenience of subsequent challenge simulation. The parameters of the model are described later, and the parameters of the model include initialization parameters and input parameters, and the initialization parameters mainly serve to initialize the model and set the initialization parameters of the model. The parameter to be initially set only needs to be set once, and does not need to be set at each resolving.
All or part of input parameters required by the model are transmitted to the model entity through the data input and output parameters at one time. Similarly, the data output interface transmits the data required to be output to the engine by the entity in the current frame at one time through the same data structure. The interfaces of the model are shown in FIG. 7:
step 204: the transmitted signal is amplified by the transmitting antenna, and noise, including transmission loss (free space loss, atmospheric transmission loss), system thermal noise, and external interference, is introduced during propagation and then received by the receiving antenna. The bit error rate of the link can be calculated through the signal-to-noise ratio.
Since the communication equipment is usually mounted on other carriers such as airplanes and armored cars, the directional angle and the elevation angle of the antenna are relative to the body coordinate system, and in the process of performing link solution, solution needs to be performed under the ground coordinate system, and therefore, coordinate conversion is needed. The transformation equation from the ground coordinate system S _ g to the body coordinate system S _ b is as follows
Assuming that the antenna is coincident with the body axis, the height angle and the direction angle of the pointing direction of the antenna are both 0, and the antenna is regarded as a rigid body, the coordinates of a certain point of the antenna under the body coordinate system are as follows:
it is converted into coordinates in the ground coordinate system:
it can then be derived that the antenna points at a direction angle and a height angle relative to the ground coordinate system:
the third step: a mission-level model of the communication system is designed, military communication network simulation is performed, and the military communication network simulation flow is shown in fig. 4. To meet the real-time nature of military communication network simulation, the mission-level model temporarily does not consider directionality, and only calculates the coverage of communication. The communication network between different units on the battlefield is mainly represented as a tactical internet, the tactical internet generally adopts an ad hoc network, the ad hoc network simulation calculation calculates the indexes of packet loss rate, first packet arrival time, delay time and the like of the whole communication network by means of communication network simulation software, and the communication network simulation flow is shown in fig. 4.
Step 301: and establishing a task-level model of the communication system, and only considering the coverage range of the equipment by only needing the fixed antenna gain of the facility without considering the directivity of the communication equipment in order to meet the real-time performance of the communication network simulation during the simulation resistance.
Step 302: as shown in fig. 4, a simulation scenario is set by a TCL script, the TCL script may set an interface to receive externally input data, may receive data planned by simulation, such as location information of a node, and then sets a step length, and analyzes an effect of a tactical internet by analyzing an obtained tr file when a time length of a simulation step length is really one at a time. The transmission model for ns2 is coarse and therefore the loss model for ns2 as well as the antenna model can be modified and therefore linked to models of other granularity already established. The specific meaning of the parameters of the wireless communication network is shown in table 7:
table 7 parameter specific meanings of wireless communication networks
When setting the node positions in the TCL script, the node positions may be written in a form capable of receiving external input in real time, and besides, the antenna gain may also receive input of an externally established model rather than being manually set, and since the antenna gain can be set only once and cannot be set for each node individually, an average value of the entire network gain may be received.
After the simulation scenario is run, the result may be saved in a tr file, where the meaning of each column in the tr file is shown in table 8:
and calculating the indexes of the packet loss rate, the first packet arrival time, the delay time and the like of the whole communication network by analyzing the tr file.
Step 303: since ns2 needs to run in a linux environment, socket communication is required to be connected with a model running in a windows environment. The simulation step size is first set, where the time at which the CBR starts to transmit and ends can be set to the simulation step size by external input, e.g., 0.2s. Then, every 0.2s of simulation time, the external model transmits information such as the position of the node at the moment to the linux environment through the socket, and the tcl file controls ns2 to perform 0.2s simulation. A combat simulation program running in Windows is used as a Client program Client, a program which is run in a Linux environment and calls ns2 to carry out tactical Internet simulation is used as a Server, and the Client transmits information which needs to be transmitted to tcl script control ns2 simulation to a Server end every other simulation step length. After receiving the information, the Server end creates a sub-process, calls a system function system (ns x tcl), and starts ns2 simulation of a simulation step. Each simulation stores the simulation result in a tr file,
the fourth step: a model of the impact of a typical battlefield environment on communications is established. Typical battlefield environments include natural environments and artificial environments, the natural environments include atmospheric environments and topographic environments, the atmospheric environments include oxygen and water vapor absorption models, and the topographic environments calculate the influence of topographic elevation data on electromagnetic wave propagation visibility. The artificial environment is an interference machine model, and the influence of active suppression interference on communication is calculated.
Step 401: firstly, an atmospheric environment model of a battlefield is established. Atmospheric absorption losses include absorption losses of oxygen and water vapor, and tropospheric atmospheric pressure P, temperature T and water vapor density ρ are plotted against height h according to the us standard atmospheric model as follows:
where α =52561222, β =0.034164794, r _0is the earth radius (m), h is the altitude (m), T is the temperature (K), and the water vapor density of the troposphere is as follows:
wherein h is height, c i Is constant and can be found by looking up relevant literature.
Besides the tropospheric atmosphere model, there is also an absorption effect of tropospheric oxygen on electromagnetic waves, and therefore an oxygen absorption factor model is to be established. Tropospheric oxygen absorption for electromagnetic waves is the sum of many resonance line absorptions around 60 GHz. The expression of the absorption factor of oxygen for electromagnetic waves of an arbitrary frequency f is as follows:
in the formula, A N Is the summation term of each resonance number N.
Wherein the summation term of each resonance number N is as follows:
in the formula (I), the compound is shown in the specification,
the tropospheric water vapour absorption is divided into two parts: resonance at 22.235GHz, absorption factor xi _22 (h) and side effects of resonance lines above 100GHz, absorption factor xi _ res (h)
In the formula (I), the compound is shown in the specification,
f is the frequency effect.
The atmospheric absorption loss model can be connected with an engineering-level model and a functional-level model in the form of noise loss, and can be added into the ns2 transmission model and recompiled, so that the ns2 transmission loss is more accurate.
Step 402: and establishing a visibility model of the terrain. The method comprises the steps of regarding the earth as a plane, determining a viewpoint and a target point under a plane earth coordinate system, projecting a sight line on an xoy plane, uniformly acquiring a plurality of sampling points on a projection line, inquiring DEM data to obtain the elevation of each sampling point, and judging the visibility of the viewpoint and the target point.
Taking a plurality of sampling points between the viewpoint and the target point, starting from the sampling point 1, if the slope of the connecting line of the viewpoint and the sampling points is smaller than the slope of the sight line, indicating that the current sampling point does not influence the communication, and advancing to the next sampling point to continuously compare the slopes;
and if the slope of the connecting line of the viewpoint and a certain sampling point is greater than that of the sight, the viewpoint and the target point cannot see through, and the calculation is finished. If the target point can be pushed all the way forward, the perspective between the viewpoint and the target point can be shown.
Step 403: and establishing an interference machine model. In free space, the environment of the device to be interfered is close to idealization, the sending and receiving signals do not receive any interference, and the coverage area of the device to be interfered is determined by the ratio between the noise generated in the receiver and the target echo power intensity. Wherein, the target echo power intensity is as follows:
in the formula, P t To transmit power, G t For transmitting antenna gain, G r For receive antenna gain, λ is the wavelength and R is the distance.
The average power strength of the thermal noise of the receiver of the device to be interfered is as follows:
N＝kT 0 B r F
the signal-to-noise ratio in free space is:
wherein K is Boltzmann's constant, T 0 As the receiver noise temperature, B r F is the receiver noise figure for the receiver bandwidth.
Under the active suppression interference, the interference power strength of the receiver of the device to be interfered is as follows:
the gain of the interfering device antenna in the direction of the interferer is:
in the formula, theta 0. For the main board gain of the receiver antenna, theta is the line connecting the transmitter and the receiver andand an included angle between connecting lines of the receivers of the jammers, K is a constant, and the value is taken according to the performance parameters of the receivers.
In the case of active suppressed interference, the signal-to-interference ratio at the receiver output is calculated as follows:
in the formula, P x The signal power is received for the receiver.
The established jammer parameters are shown in table 9:
TABLE 9 jammer parameters
In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, are merely for convenience of description of the present invention, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.
Claims (7)
1. A multi-granularity modeling real-time simulation method for a communication system in countermeasure simulation is characterized by comprising the following steps:
s1, according to the performance index requirement of antenna design, obtaining offline power directional diagram data of an antenna by using electromagnetic simulation software, processing the power directional diagram data into a three-dimensional directional diagram, and performing online interpolation to obtain online continuous data;
s2, constructing a link calculation simulation model, and establishing an engineering-level model and a functional-level model; then, the calculation of the antenna gain is obtained by an engineering-level model based on online continuous data in a mode of off-line calculation and online interpolation in the first step; after the maximum gain of the antenna is obtained by adopting an empirical formula in the functional level model, the inherent parameters of the antenna are utilized to calculate the main lobe, half-power beam width, side lobe gain and back lobe gain of the antenna according to an antenna directional diagram, so that the directivity of the antenna is described;
s3, establishing a task-level model in the link resolving simulation model, performing military communication network simulation, and only calculating the coverage area of communication;
s4, establishing a model of the influence of a typical battlefield environment on communication, wherein the model comprises the following steps: a battlefield atmospheric environment model, a terrain visibility model and an interference machine model;
wherein the granularity of the engineering-level model, the functional-level model and the task-level model is from fine to coarse.
2. The method of claim 1, wherein the typical battlefield environment comprises: the natural environment comprises an atmospheric environment and a topographic environment, and the atmospheric environment comprises oxygen and water vapor;
the battlefield atmospheric environment model is used for calculating the influence of the absorption loss of oxygen and water vapor in the battlefield atmospheric environment model on the electromagnetic wave propagation;
the terrain visibility model is used for calculating the influence of terrain elevation data in the terrain environment on electromagnetic wave propagation;
the interference machine model is used for calculating the influence of active suppression interference on communication in the artificial environment.
3. The method according to claim 1, wherein the function-level model is provided with an output port for implementing at least one of the following functions: obtaining the signal frequency of the transmitting equipment, the bandwidth of the transmitting equipment, the transmitting gain of the transmitting equipment, the transmitting power of the transmitting equipment, the position of the transmitting equipment, the communication result of the link and the error rate of the link;
the function level model is provided with an input port for implementing at least one of the following functions: inputting the position of a model, inputting the interference power, inputting the transmission parameters of the equipment to be received and inputting the attitude angle of a carrier carried by the equipment.
4. The method according to claim 1, wherein the step S1 specifically includes:
s101, resolving an antenna physical field to obtain three-dimensional field intensity directional diagram data of an antenna two-dimensional gain directional diagram;
s102, calculating field intensity data of the referenced ideal isotropic antenna, then calculating an absolute gain value of each point, and finally obtaining three-dimensional gain directional diagram data of the antenna;
and S103, interpolating by adopting a bidirectional interpolation algorithm according to the antenna three-dimensional gain directional diagram data obtained in the step S102 to obtain continuous data required in the simulation process.
5. The method according to claim 1, wherein the step S2 includes:
s201, calculating the maximum gain of the typical aperture antenna based on an empirical formula of the maximum gain of the typical aperture antenna, obtaining the half-power beam width, the side lobe gain and the back lobe gain according to the inherent parameters of the antenna and an antenna directional diagram of online continuous data, and describing the directivity of the antenna;
s202, calculating free space loss in the transmission process and noise loss including system thermal noise and variables of a typical battlefield environment;
s203, modeling the function level model, and transmitting 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 transmitting the data required by the function level model to be output to an engine in the current frame in a signal mode;
s204, the signal is transmitted after being amplified by the transmitting antenna and received by the receiving antenna, the error rate of the link is calculated through the signal-to-noise ratio, and the direction angle and the altitude angle of the antenna pointing direction relative to a ground coordinate system are obtained through coordinate conversion based on the directivity of the antenna.
6. The method according to claim 1, wherein the step S3 specifically includes:
s301, establishing a task-level model of the communication system;
s302, performing military communication network simulation by using ns 2;
and S303, carrying out socket communication to enable ns2 running in the linux environment to be connected with the model running in the windows environment.
7. The method according to claim 6, wherein the step S4 specifically includes:
s401, establishing a battlefield air environment model, and establishing a battlefield atmospheric environment model comprising variables of absorption factors of oxygen and water vapor on electromagnetic waves;
s402, establishing a terrain visibility model, acquiring a plurality of sampling points of the projection of the sight between the viewpoint and the target point on the xoy plane, and judging the size of the slope of the connecting line of the viewpoint and the sampling points and the slope of the sight and the visibility between the viewpoint and the target point;
s403, establishing an interference machine model, wherein the interference machine model comprises target echo power intensity, average thermal noise power intensity of a receiver of the device to be interfered, signal-to-noise ratio in free space, interference power intensity of the receiver of the device to be interfered under active suppression interference, gain of an antenna of the interference device in the direction of the interference machine, and variables of signal-to-interference ratio of an output end of the receiver under the active suppression interference.
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