CN115436891A - MBSE-based model construction radar countermeasure evaluation method - Google Patents
MBSE-based model construction radar countermeasure evaluation method Download PDFInfo
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Abstract
The invention discloses a method for evaluating radar countermeasure effect by model construction based on MBSE (multi-beam radar SE). A system engineering method based on a model is adopted, and the model construction is characterized and designed based on the detection principle of radar countermeasure. The model design is researched from a radar equation, an interference signal modulation mode, an interference effect and the like respectively, user requirements and function requirements of the model are analyzed, the design is driven by the requirements, the composition and the performance of the overall model are optimized integrally, and the consistency among the requirements, the functions and the model is ensured. The invention utilizes the model construction method based on MBSE to uniformly and cooperatively design the countermeasure model, and can effectively realize the design and simulation of the radar countermeasure model and the evaluation of the countermeasure effect under the existing condition.
Description
Technical Field
The invention belongs to an information processing technology, and particularly relates to a radar countermeasure evaluation method established based on an MBSE model.
Background
At present, electronic warfare has gradually led to the trend of information countermeasure, and radar countermeasure is continuously and intensively studied by researchers as an important part thereof. Because the radar has the advantages of large action range and high range resolution, the radar is widely applied to actual combat, and the research on the skilled operation of a radar system and the radar data processing is more and more important. With the continuous development of modern radar technology, radar systems become increasingly complex both in terms of composition and performance, which results in high cost for practical operation of the radar system, and it is also difficult to perform data analysis based on the obtained radar countermeasure data. Therefore, the evaluation of the radar countermeasure effect by using the model construction becomes an essential link in the development of the current radar technology. The radar countermeasure model construction is that different types of radar countermeasure simulation models are constructed according to a radar countermeasure principle to flexibly form a radar countermeasure environment, the countermeasure effect is contrastively analyzed and evaluated according to simulation data, and simulation data basis and tactical formulation strategy are provided for actual countermeasure.
In the construction process of the radar countermeasure model, a system engineering method is mainly adopted for design, so that on one hand, the composition and the performance of the model are optimized and overall, meanwhile, factors related to the radar countermeasure model in each model and the coordination relationship among all components are comprehensively considered, analyzed and researched, and the model construction is effectively carried out and the optimal performance is achieved.
The traditional radar countermeasure model is mainly constructed by a file-based system engineering method. By file-based, it is meant that during the model development process, all system engineering designs or specifications are recorded in documents via natural language, the outcome of each engineering activity is a document, which may be in paper or electronic format, and then communicated and interacted with in each engineering activity using the documents. The document describes the requirement and design information required by each activity, and all the activities are uniformly and orderly carried out according to the document, so that the rigor of the development process is ensured. However, the file-based method has problems of inaccurate and incomplete description or ambiguity in the process of using natural language, poor traceability and alteration effect evaluation, and insufficient and accurate description for system requirements and design requirements.
Disclosure of Invention
The invention provides an MBSE (multi-function space) based model construction radar countermeasure effect evaluation method, which starts from the detection principle of radar countermeasure, takes an MBSE visual data model as a basis, characterizes the model construction process from 3 aspects of requirement analysis, function decomposition and model generation, and ensures the consistency of information transmission among requirements, functions and models. And (4) designing a requirement analysis driving function decomposition in the early stage, generating a bearing system function by the model, and realizing the design of the model through optimization iteration. The model design is researched from a radar equation, an interference signal modulation mode, an interference effect and the like respectively, a radar countermeasure model is built, and the evaluation of the countermeasure effect is achieved.
The technical solution for realizing the invention is as follows: an MBSE-based model construction radar countermeasure evaluation method comprises the following steps:
step 1, carrying out demand analysis on the radar countermeasure model.
And 2, designing a functional architecture of the radar countermeasure model based on the functional requirements of the countermeasure model obtained by the requirement analysis result of the radar countermeasure model.
Step 3, designing a radar model according to the designed countermeasure model functional architecture:
according to various requirements on the functions of the radar model, the radar model comprises a data input submodule, an antenna simulation submodule, a radar signal processing submodule, a data generation submodule, a power generation submodule and a data output submodule.
And 4, designing a target model according to the input parameters.
And 5, judging the design of an interference model according to whether the input parameters have interference, if so, performing the step 6, and otherwise, directly performing the step 7.
And 6, designing an interference model according to the input parameters.
And 7, obtaining a radar countermeasure model according to the radar model, the target model and the interference model, and evaluating the radar countermeasure effect.
Compared with the prior art, the invention has the remarkable advantages that:
and aiming at radar countermeasure effect evaluation, a model construction is designed by adopting a model-based system engineering method. Aiming at the design of a radar countermeasure model, user requirements and functional requirements of an analysis model are researched, the countermeasure model is designed in a demand-driven mode, unified and collaborative mode is designed, and a design scheme is guaranteed to meet the requirements and can meet design requirements. Under the existing condition, the design and simulation of a radar countermeasure model and the evaluation of the countermeasure effect can be effectively realized.
Drawings
Fig. 1 is a block diagram of a radar countermeasure model according to the present invention.
Fig. 2 is a flow chart of the working process of the radar countermeasure model function module of the invention.
FIG. 3 is a block diagram of the design of the radar model of the present invention.
Fig. 4 is a block diagram of the interference model design of the present invention.
Fig. 5 is a block diagram of an antenna simulation submodule according to the present invention.
Fig. 6 is a diagram of the single radar interference countermeasure of the present invention.
Fig. 7 is a diagram of multiple radar interference rejection graphs in accordance with the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
The following further introduces specific embodiments, technical difficulties and inventions of the present invention with reference to the design examples.
With reference to fig. 1 to 5, the method for evaluating the radar countermeasure effect based on the model construction of the MBSE according to the present invention includes the following steps:
step 1, carrying out demand analysis on the radar countermeasure model. The key to the model-based system engineering design approach is driven by requirements. If the function of the countermeasure model can be completely realized, the first link is to perform demand analysis on the radar countermeasure model, and the functional demand of the radar countermeasure model is used as the guidance basis of model design. Firstly, starting from the requirements of users, analyzing and researching the expectations of the users for the confrontation model and the use functions which can be completed by the model, organizing the activities of the complete users and the interaction behaviors and data between the complete users and the model, and describing the use scenes and participants of the confrontation model. For the radar countermeasure model, the external participants mainly include a radar operator, a decision maker, a jammer operator and a target. The user requirements of the model are the requirements of the participants, and mainly include radar discovery targets, radar discovery targets interfered by the jammers, self requirements of detection realized by the radars, self requirements of interference realized by the jammers and the like.
After user requirements of the radar countermeasure model are obtained, the functional requirements of the model are determined by analyzing the implementation requirements and the implementation process of the requirements. Based on the application purpose and characteristics of the radar countermeasure model, the functions of the model can be determined, namely the detection function of the radar on the target, various interference functions of the jammer on the radar and the motion generation function of the target can be realized.
And further designing the function of the model according to the functional requirement of the radar countermeasure model. In combination with the functional requirements, the functional module must have both signal level and functional level simulation functions during the design process, and can adopt the functional module adapted to different application scenarios and requirements. Meanwhile, the functional modules also need to have configurability, and can dynamically combine and configure corresponding modules according to different types of simulation requirements to realize configurable confrontation simulation. In addition, each functional module needs to simulate the real situation as accurately as possible, so as to ensure the effectiveness of the countermeasure simulation.
And 2, designing a functional architecture of the radar countermeasure model based on the functional requirements of the countermeasure model obtained by the requirement analysis result of the radar countermeasure model. The radar countermeasure model is mainly divided into three modules, namely a parameter setting function module, a model simulation function module and a model output function module, on the function module to construct an countermeasure model, wherein the model simulation function module establishes 4 models including a radar countermeasure model, an interference model, a target model and an environment model, and the radar countermeasure model function module is shown in figure 1.
With reference to fig. 2, the radar countermeasure model is functionally decomposed into three functional modules, a parameter setting functional module, a model simulation functional module, and a model output functional module. The three modules provide detailed and definite function description for the confrontation model, completely design the module composition of the confrontation model and the function interaction among the modules, and lay a foundation for the subsequent modeling realization.
The three modules of the parameter setting function module, the model simulation function module and the model output function module are respectively divided into labor and have the following functions:
the parameter setting function module receives external model setting parameters through an external interface, judges the effectiveness of the setting parameters according to the type of a required model and the effective range of the model parameters, and simultaneously calls relevant parameters and data information of model calculation and transmits the relevant parameters and data information to the model simulation function module for simulation calculation.
The model simulation function module mainly selects a corresponding simulation model according to simulation data information given by the parameter setting function module, calls related simulation calculation, obtains real-time state and performance parameters of the model, and transmits the real-time state and performance parameters to the model output function module.
The model output function module receives data parameters transmitted by the model simulation function module, classifies and arranges the data parameters according to output requirements, can transmit the data parameters to other subsystems through an external interface for use, can also be stored in a database for other model calculation and use, and can arrange the data parameters to form visual data for output and display.
And 3, designing a radar model according to the designed countermeasure model functional architecture. According to various requirements on the functions of the radar model, the radar model design mainly comprises a data input submodule, an antenna simulation submodule, a radar signal processing submodule, a data generation submodule, a power generation submodule and a data output submodule, and the number of the data input submodule, the antenna simulation submodule, the radar signal processing submodule, the data generation submodule, the power generation submodule and the data output submodule is 6.
With reference to fig. 3, the modules are designed as follows:
a data input sub-module: the method mainly receives model setting parameters and data input from the outside, system parameters required by model simulation, control parameters of radar operation and parameters and data required by calculation involved in the model simulation process.
An antenna simulation submodule: and according to the received antenna parameters, such as rotating speed, steering mode, rotating direction and the like, the simulation of the radar antenna system is realized. Antenna transmission and reception gains for targets within the detection range are calculated through simulation of antenna patterns and antenna motion. The implementation block diagram of the antenna simulation submodule is shown in fig. 5.
A radar signal processing submodule: the method mainly comprises pulse compression, signal detection, trace point estimation and the like. Pulse compression techniques typically use matched filtering to achieve processing of large time-bandwidth signals such as chirp. The matched filter is the best filter based on the criterion of outputting the maximum signal-to-noise ratio. The signal-to-noise ratio of the system is further improved through the processing of the pulse pressure.
Assuming a passive filter is used, the pulse width after the filter is τ =1/B, B is the input signal bandwidth, and the gain obtained by the signal is:
Gain＝B·τ (1)
where P is the signal power and Gain is the Gain obtained by the signal.
The distance spectrum of the baseband signal can be obtained after the target echo signal is subjected to pulse compression processing, then the target is detected according to a certain threshold value by utilizing signal detection processing, and the trace point parameter of the target is estimated.
A data generation submodule: the method mainly aims at processing a target track, including track generation, track association and track tracking, and can accurately establish the track and keep track tracking on the target when the target enters a detection range, and meanwhile, false tracks caused by clutter, interference and other factors can be avoided as much as possible. ByA plurality of estimation values generated in the signal processing process of the radar signal processing sub-module are used as a plurality of observation values of the current radar batch, wherein the estimation values comprise real targets and false targets, so that the method eliminates the multiple values through the correlation processing of the existing flight paths. During track association processing, the state estimation of the nearest moment n of a target track is taken as the circle center, an association threshold is set, and a truncated sector association area Q is established by taking the threshold as the basis n And if any value in the obtained estimation values falls into the associated area, the estimation value and the existing track of the target form an associated hypothesis.
Q n ＝Span(r n max ,r n min ,α n max ,α n min ) (2)
Wherein Span (. Cndot.) is sector, r nmax And r nmin Respectively corresponding to the outer circle radius and the inner circle radius of the sector-shaped associated area at the moment n, alpha nmax And alpha nmin The maximum azimuth and the minimum azimuth corresponding to the sector respectively, wherein:
in the formula, r n And alpha n The predicted estimated values r of the distance and the direction of the target track at the next moment are respectively corresponding i ' and r i Corresponding respectively to the measured and estimated values of the distance, alpha, at the moment of the target track i ' and alpha i The weighting coefficients are respectively corresponding to the mean square error and deviation between the distance measurement value and the estimation value, v and x are respectively corresponding to the mean square error and deviation between the orientation measurement value and the estimation value, and i is the serial number of the sector associated area.
A power generation submodule: the radar action range can be calculated in real time according to radar working parameters, environmental parameters, meteorological parameters, geographic information parameters and the like, and a radar power coverage area is generated. The basis of radar is to find and locate the target, and thus, the maximum detection range R max Is an important performance index of radarOne, it can be represented as:
in the formula, P R Is the transmission power of radar, G R For radar antenna gain, λ is radar wavelength, σ is target scattering cross-sectional area, SNR min Is the minimum detectable power.
A data output submodule: the radar data output submodule can output signal-level and functional-level simulation data according to the simulation requirements of the model.
And 4, designing a target model according to the input parameters. If the transmitting signal of the radar is LFMCW, the basic form S (t) of the transmitting signal is as follows:
wherein f is 0 Is the initial frequency of the signal, T is the frequency modulation period, alpha is the frequency modulation slope, theta 0 The amplitude of the signal transmitted by A is the initial phase, t is time, k is the number of frequency modulation cycles, and j is an imaginary unit.
Target echo signal S r (t) can be expressed as:
wherein τ is a signal delay when an echo reaches a radar receiver, τ =2R/c, R represents a distance between a target and a radar, c is a speed of light, a r Is the target echo signal amplitude.
And 5, judging the design of an interference model according to whether the input parameters have interference, if so, performing the step 6, and otherwise, directly performing the step 7.
And 6, designing an interference model according to the input parameters. The interference model design comprises a data input module, an interference generation module and a data output module, as shown in fig. 4.
The interference generation module generates squashed interference and deceptive interference. The suppression type interference is mainly realized by transmitting a high-power interference signal to enter a radar receiver, so that the signal-to-noise ratio of a target echo signal is greatly reduced, and the radar target detection is difficult. Interference signal power P received by radar under suppression interference condition rj Can be expressed as:
in the formula, P j For jammers transmitting power, G j Antenna gain for jammers in the radar direction; g r Antenna gain for radar in jammer direction; λ is the radar wavelength; r is j The distance from the jammer to the radar; and L is interference signal loss in the transmission process.
Maximum detection distance R of radar under interference condition max Can be expressed as:
in the formula, P R For the transmission power of radar, G R For radar antenna gain, λ is radar wavelength, σ is target scattering cross-sectional area, SNR min For the minimum detectable power, P rj Is the interference signal power received by the radar.
The deceptive jamming is mainly to generate jamming signals containing false target information to act on the radar, so that the radar can not find a real target or correctly obtain real parameters of the target, and the purposes of confusing and disturbing radar target detection and tracking are achieved. Assuming that the echo signal X (t) of a real target can be expressed as:
wherein A is T Amplitude of echo signal for real targetAnd f is the echo signal frequency of the real target.
The interference signal containing the spurious range information can be described by a signal delayed with respect to the target echo signal:
in the formula, J s (t) is an interference signal containing false distance information, A j To the interference signal amplitude, Δ t is the signal delay corresponding to the false distance information.
An interfering signal containing spurious velocity information may be considered to be a signal having a doppler frequency shift Δ f relative to a target echo signal, i.e. a signal having a doppler frequency shift Δ f
Wherein, J v (t) is an interference signal containing spurious speed information.
And 7, designing a radar model, a target model and an interference model according to the steps 2 to 6, and designing a radar countermeasure model for evaluation.
The radar countermeasure effect evaluation method is established by using an MBSE (model based on least significant space) model provided by an article, experimental verification and inspection are carried out by mutual countermeasure of a radar system simulated by the model and an interference system, the authenticity of the radar countermeasure effect is close to the actual situation through the algorithm of the text, the model design efficiency is high, the user requirements can be met, and the result is shown in fig. 6 and 7.
Claims (7)
1. An MBSE-based model construction radar countermeasure evaluation method is characterized by comprising the following steps:
step 1, carrying out demand analysis on a radar countermeasure model;
step 2, designing a functional architecture of the radar countermeasure model based on the functional requirements of the countermeasure model obtained by the requirement analysis result of the radar countermeasure model;
and 3, designing a radar model according to the designed countermeasure model functional architecture:
according to various requirements on the functions of the radar model, the radar model comprises a data input sub-module, an antenna simulation sub-module, a radar signal processing sub-module, a data generation sub-module, a power generation sub-module and a data output sub-module;
step 4, designing a target model according to the input parameters;
step 5, carrying out interference model design judgment according to whether the input parameters have interference, if so, carrying out step 6, otherwise, directly carrying out step 7;
step 6, designing an interference model according to the input parameters;
and 7, obtaining a radar countermeasure model according to the radar model, the target model and the interference model, and evaluating the radar countermeasure effect.
2. The method for evaluating the radar countermeasure effect based on the MBSE model construction as set forth in claim 1, wherein in step 1, the demand analysis is performed on the radar countermeasure model, specifically as follows:
taking the functional requirements of a radar countermeasure model as a guide basis of model design, firstly, analyzing and researching the expectation of a user on the countermeasure model and the use function which can be completed by utilizing the model from the requirements of the user, finishing the activities of the complete user and the interaction behaviors and data between the complete user and the model, and describing the use scene and participants of the countermeasure model; for the radar countermeasure model, external participants mainly comprise a radar operator, a decision maker, an interference machine operator and a target; the user requirements of the model are the requirements of the participants, and the requirements comprise radar finding targets, jammer interference radar finding targets, radar detection realization self requirements and jammer interference realization self requirements;
after user requirements of a radar countermeasure model are obtained, functional requirements of the model are determined by analyzing implementation requirements and implementation processes of the requirements; based on the application purpose and characteristics of the radar countermeasure model, the function of the clear model is to realize the detection function of the radar on the target, various interference functions of the jammer on the radar and the motion generation function of the target;
according to the functional requirements of the radar countermeasure model, further carrying out functional design on the model; combining with functional requirements, the functional module must have both signal level and functional level simulation functions in the design process, so as to adopt the functional module adapted to different application scenarios and requirements; meanwhile, the functional modules also need to have configurability, and corresponding modules can be dynamically combined and configured according to different types of simulation requirements so as to realize configurable confrontation simulation; in addition, each functional module needs to simulate the real situation as accurately as possible, so as to ensure the effectiveness of the counter simulation.
3. The method for evaluating the radar countermeasure effect of model construction based on MBSE according to claim 2, wherein in step 2, based on the functional requirements of the countermeasure model obtained from the results of the requirement analysis performed by the radar countermeasure model, the functional architecture of the radar countermeasure model is designed as follows:
the radar countermeasure model is decomposed into three functional modules according to functions: the device comprises a parameter setting function module, a model simulation function module and a model output function module;
the parameter setting function module receives external model setting parameters through an external interface, judges the effectiveness of the setting parameters according to the type of a required model and the effective range of the model parameters, calls relevant parameters and data information of model calculation, and transmits the relevant parameters and data information to the model simulation function module for simulation calculation;
the model simulation function module selects a corresponding simulation model according to the simulation data information given by the parameter setting function module, calls related simulation calculation, obtains the real-time state and performance parameters of the model, and transmits the real-time state and performance parameters to the model output function module;
the model output function module receives data parameters transmitted by the model simulation function module, classifies and arranges the data parameters according to output requirements, can transmit the data parameters to other subsystems for use through an external interface, can store the data parameters in a database for calculation of other models, and can arrange the data parameters to form visual data for output and display.
4. The MBSE-based model building radar countermeasure evaluation method according to claim 3, wherein in the step 3, according to various requirements on the radar model function, the radar model comprises a data input sub-module, an antenna simulation sub-module, a radar signal processing sub-module, a data generation sub-module, a power generation sub-module and a data output sub-module, which are specifically as follows:
a data input sub-module: the system comprises a model simulation system, a radar simulation system, a model setting module, a radar simulation module and a control module, wherein the model setting module is used for receiving model setting parameters and data input from the outside, system parameters required by the model simulation, control parameters of the radar operation and parameters and data required by calculation involved in the model simulation process;
an antenna simulation submodule: according to the received antenna parameters, the simulation of the radar antenna system is realized; calculating antenna transmitting and receiving gains aiming at a target in a detection range through simulation of an antenna directional diagram and antenna movement;
a radar signal processing sub-module: pulse compression, signal detection and trace point estimation are included;
a data generation submodule: processing a target track, including track generation, track association and track tracking, so that the track can be accurately established and the track tracking of the target can be maintained when the target enters a detection range, and false tracks caused by clutter and interference factors can be avoided as much as possible;
during track association processing, the state estimation of the nearest moment n of the target track is taken as the circle center, an association threshold is set, and a truncated sector association area Q is established based on the association threshold n And if any value in the obtained estimation values falls into the associated area, forming an associated hypothesis by the estimation value and the existing track of the target:
Q n ＝Span(r nmax ,r nmin ,α nmax ,α nmin ) (2)
wherein Span (. Cndot.) is sector, r nmax And r nmin Respectively corresponding to the outer circle radius and the inner circle radius of the sector associated region at the moment n, alpha nmax And alpha nmin Respectively corresponding to the most sectorA large azimuth angle and a minimum azimuth angle, wherein:
in the formula, r n And alpha n The predicted estimated values r of the distance and the direction of the target track at the next moment are respectively corresponding i ' and r i Corresponding respectively to the measured and estimated values of the distance at the moment of existence of the target track, alpha i ' and alpha i The weighting coefficients are respectively corresponding to the mean square error and the deviation between the distance measured value and the estimated value, v and x are respectively corresponding to the mean square error and the deviation between the orientation measured value and the estimated value, and i is the serial number of a sector association area;
a power generation submodule: the radar action range can be calculated in real time according to radar working parameters, environmental parameters, meteorological parameters and geographic information parameters, and a radar power coverage area is generated;
the data output submodule: and outputting signal-level and functional-level simulation data according to the simulation requirements of the model.
5. The MBSE-based model construction radar countermeasure evaluation method according to claim 4, wherein in the step 4, a target model is designed according to input parameters, and the method comprises the following specific steps:
if the transmitting signal of the radar is LFMCW, the basic form S (t) of the transmitting signal is as follows:
wherein f is 0 Is the signal starting frequency, T is the frequency modulation period, alpha is the frequency modulation slope, theta 0 The method comprises the following steps that A is an initial phase, A is a transmission signal amplitude, t is time, k is the number of frequency modulation cycles, and j is an imaginary number unit;
the target echo signal S r (t) is expressed as:
wherein τ is a signal delay when an echo reaches a radar receiver, τ =2R/c, R represents a distance between a target and a radar, c is a speed of light, a r Is the target echo signal amplitude.
6. The MBSE-based model building radar countermeasure evaluation method of claim 5, wherein in the step 6, the interference model design comprises a data input module, an interference generation module and a data output module, and the interference generation module is used for generating suppressing interference and deceptive interference.
7. The MBSE-based model building radar countermeasure evaluation method of claim 6, wherein:
interference signal power P received by radar under suppression interference condition rj Expressed as:
in the formula, P j For jammers transmitting power, G j Antenna gain for jammers in the radar direction; g r Antenna gain for the radar in the jammer direction; λ is the radar wavelength; r is j The distance from the jammer to the radar; l is interference signal loss in the transmission process;
maximum detection distance R of radar under interference condition max Expressed as:
in the formula, P R Is the transmission power of radar, G R For radar antenna gain, λ is radar wavelength, and σ is eyeStandard scattering cross-sectional area, SNR min For the minimum detectable power, P rj Is the interference signal power received by the radar;
suppose that the echo signal X (t) of a real target is represented as:
wherein, A T The amplitude of the echo signal of the real target, and f is the frequency of the echo signal of the real target;
the interference signal containing the false distance information is described by a signal with a delay relative to the target echo signal:
in the formula, J s (t) is an interference signal containing false distance information, A j The amplitude of the interference signal is, and delta t is the signal delay corresponding to the false distance information;
the interfering signal containing the spurious speed information is regarded as a signal having a Doppler frequency shift Deltaf relative to the target echo signal, i.e.
Wherein, J v (t) is an interference signal containing spurious speed information.
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