CN114384476B - Self-adaptive interference signal generation method based on interference strategy guidance - Google Patents
Self-adaptive interference signal generation method based on interference strategy guidance Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/38—Jamming means, e.g. producing false echoes
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Abstract
The invention discloses a self-adaptive interference signal generation method based on interference strategy guidance, which comprises the steps of prior work scene matching, space signal investigation and classification, target threat level sequencing, interference type matching, interference generation and the like in the implementation process.
Description
Technical Field
The invention belongs to a self-adaptive interference signal generation method, and particularly relates to a self-adaptive interference signal generation method in a complex electromagnetic environment.
Background
Under the trend of high informatization of battlefield environment and increasing electronization of weapon equipment, radar interference equipment becomes one of main combat means for weakening and destroying the efficiency of an enemy radar system, and the war progress and the ending are directly related. The application of the interference equipment comprises that an enemy radar and a communication system are interfered to make the enemy radar and the communication system not work normally, so as to shield an own target, intercept an enemy signal and acquire information contained in the signal from the enemy signal to provide electronic information for the own, and induce the enemy detection equipment to make false judgment and the like through means such as deception interference.
The interference resources of the radar comprise the number of the jammers in the system, the idle state of the jammers, the performance of the jammers and the like. Because the number of the jammers and the interference capability of the jammers are limited, reasonable allocation of interference resources in the system is needed through interference resource scheduling so as to achieve the purpose of efficiently completing interference tasks.
The radar interference resource scheduling problem belongs to an important subject in radar interference. However, the research of radar interference is usually focused on the technical level, and the tactical feasibility is not considered enough. Scheduling of radar interference resources, decoy, timing of interference, etc. are difficult to grasp, and effective interference countermeasures cannot be provided in real time. Therefore, it is necessary to design a real-time investigation on electromagnetic environment, to continuously perfect an interference countermeasure resource scheduling library, and to update the target threat level ranking, so as to find an optimal interference release strategy, and to achieve the purpose of interfering enemy investigation and communication equipment.
Disclosure of Invention
The invention provides a self-adaptive interference signal generation method based on interference strategy guidance, which provides effective interference countermeasures in real time.
In order to solve the technical problems, the invention provides an adaptive interference signal generation method based on interference strategy guidance, which comprises the following steps:
Step 1, interference scene matching
According to the battlefield environment or the working scene of the interference equipment, a basic interference countermeasure identification library is configured and used as a priori knowledge library;
step 2, spatial signal investigation and feature extraction
The interference system detects enemy signals in real time, sorts and identifies target signals, and extracts characteristic parameters of various target signals in the space;
Step 3, target threat level accounting
Performing target threat level accounting by evaluating the importance degree of the target characteristic parameters, and adopting weighted calculation, wherein the weight is the preference setting of each characteristic parameter of the signal aiming at different combat tasks, radars with different purposes and different interference strategies;
Step 4, interference policy matching
According to the threat level queue sequence, processing is started by high priority, firstly, matching is carried out on a basic interference countermeasure identification library according to the characteristic parameters of threat signals of a first priority, and the base interference countermeasure identification library is matched preferentially according to interference frequencies, and secondly, the form, the interference type and the interference duration of interference signals are obtained;
step 5, updating basic interference countermeasure identification library
If the matching is not successful within the allowable range of the matching quantization error, inputting the characteristic parameters into a basic interference countermeasure identification library as a new training sample, and reclassifying;
Step 6, interference pattern setting
Combining the target threat degree and the limiting conditions of each interference device in the interference system, after the interference countermeasure identification library is successfully matched, converting the corresponding interference generation parameters, and then issuing the interference generation parameters to the corresponding interference devices;
Step 7, interference release
And each interference generating device generates corresponding interference signals in real time according to interference condition settings, wherein the interference conditions comprise interference types, interference intensity, interference frequency bands and interference opportunities.
Further, extracting the characteristic parameters of the spatial target signal in the step 2 includes: azimuth pitch angle, signal strength, frequency, pulse duration, pulse repetition period, polarization characteristic measurement, signal form.
Further, the importance degree of the target characteristic parameter in the step 3 is evaluated by a hierarchical analysis method based on expert scoring.
Further, in step 4, trend evaluation is continuously performed in a target signal scanning period to determine countermeasures of the interference signal.
Further, in the step 5, the updating step of the basic interference countermeasure identification library is that intelligent learning is carried out by matching with the subsequent interference performance evaluation during the in-situ simulation or the semi-physical simulation; in the field application, the credibility of the basic interference countermeasure identification library is ensured by manual intervention.
The beneficial effects of the invention include:
1) Matching a priori knowledge base according to the application environment of the interference equipment, and setting an environmental signal recognition threshold value for eliminating the influence of background clutter interference of a complex scene on space investigation;
2) Measuring and classifying the space signals in a targeted manner, extracting characteristic parameters, and acquiring threat levels of all target signals;
3) According to the interference strategy, setting the weight of each characteristic parameter of the signal, and sequencing the target threat level through the weighted operation of the characteristic vector;
4) And according to the threat level priority order, matching the basic interference countermeasure identification libraries one by one, calling each interference extension in the system, and outputting corresponding interference signals. During the internal field simulation, the basic interference countermeasure identification library can be iteratively updated according to the interference effectiveness evaluation feedback mechanism.
Drawings
Fig. 1 is a flow chart of the operation of the interference policy adaptation mechanism of the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
The invention aims to provide a self-adaptive interference signal generation method based on intelligent learning and interference policy management. Firstly, matching a working scene of interference equipment according to priori knowledge, wherein the working scene is provided with a basic interference countermeasure identification library, then, collecting, identifying and classifying and managing various signals in a space through real-time investigation, extracting characteristic parameters of various channels, carrying out iterative updating on the basic interference countermeasure identification library, and carrying out threat level sequencing according to accounting of each characteristic vector weight in the interference countermeasure identification library; in the interference release process, the interference release of each interference device in the interference system is scheduled in real time according to the sequence of threat levels.
An adaptive interference signal generation method based on interference strategy guidance, which updates and matches a basic interference countermeasure identification library according to the acquisition and feature extraction of a spatial signal so as to achieve the purpose of adaptive interference release; the method comprises the following steps:
Step 1, interference scene matching
Firstly, according to the battlefield environment or the working scene of the interference equipment, a basic interference countermeasure identification library is configured and used as a priori knowledge library, so that background clutter and spatial interference in the subsequent spatial signal investigation process are eliminated, and the difficulty of extracting the spatial signal characteristics is reduced.
Step 2, spatial signal investigation and feature extraction
The space radiation source sorting is used for intelligently sorting a large number of radiation source arrival signals distributed in the frequency domain, the time domain, the space domain and the energy domain, increasing the correlation among pulses and determining the type and parameter dynamic change information of the signals by utilizing the self-adaptive rapid cluster analysis.
To improve the interference performance of the interference system, the interference target is targeted. The interference system is required to detect enemy signals in real time, sort and identify target signals, and extract characteristic parameters of various target signals in a space, wherein the characteristic parameters comprise: azimuth pitch angle, signal strength, frequency, pulse duration, pulse repetition period, polarization characteristic measurements, signal form, etc.
Step 3, target threat level accounting
In a complex electromagnetic environment, the overlapping and uncertainty of the spatial signals cause the target threat level to have a very difficult definite standard, and the system adopts a compromise ordering method to carry out weighted calculation by evaluating the importance degree of the target characteristic parameters.
ω＝(ω0,ω1,ω2,…ωn)T
The weight is the preference setting of each characteristic parameter of the signal, and different proportions can be generated for different combat tasks, radars with different purposes and different interference strategies. In complex cases, this can be obtained by means of a hierarchical analysis based on expert scoring.
Step 4, interference policy matching
And according to the threat level queue order, starting processing by high priority, firstly matching in a basic interference countermeasure identification library according to the characteristic parameters of the threat signals of the first priority, and preferentially matching according to interference frequencies, and secondly, the interference signal form, the interference type, the interference duration and the like.
And the interference strategy matching adopts an autonomous matching and decision-making assisting mode, and the autonomous matching and decision-making assisting mode and the decision-making assisting mode cooperate to autonomously complete task deployment and conversion of the interference equipment. The change rule of the target signal is periodic, but trend evaluation needs to be continuously performed in one scanning period to distinguish countermeasures of the interference signal.
Step 5, updating basic interference countermeasure identification library
If the matching is not successful within the allowable range of the matching quantization error, the characteristic parameters are input into a basic interference countermeasure identification library to be used as a new training sample for reclassifying, and the intelligent learning can be performed by matching with the subsequent interference performance evaluation during the in-situ simulation or the semi-physical simulation. In outfield applications, because of the variety of signals in complex spaces, manual intervention is required to ensure the credibility of the underlying interference countermeasure identification library.
Step 6, interference pattern setting
And after the interference countermeasure identification library is successfully matched by combining the target threat degree and the limiting conditions of each interference device in the interference system, the corresponding interference generation parameters are required to be converted and then issued to the corresponding interference devices.
Step 7, interference release
And each interference generating device generates corresponding interference signals in real time according to interference condition settings including parameters such as interference type, interference intensity, interference frequency band, interference opportunity and the like. For example: active and passive interference means such as forwarding interference, smart noise interference, multi-decoys, foil interference, etc.
The above embodiments are only limited to the explanation and description of the technical solutions of the present invention, but should not be construed as limiting the scope of the claims. It should be clear to those skilled in the art that any simple modification or substitution of the technical solution of the present invention results in a new technical solution that falls within the scope of the present invention.
Claims (5)
1. The adaptive interference signal generation method based on interference strategy guidance is characterized by comprising the following steps:
Step 1, interference scene matching
According to the battlefield environment or the working scene of the interference equipment, a basic interference countermeasure identification library is configured and used as a priori knowledge library;
step 2, spatial signal investigation and feature extraction
The interference system detects enemy signals in real time, sorts and identifies target signals, and extracts characteristic parameters of various target signals in the space;
Step 3, target threat level accounting
Performing target threat level accounting by evaluating the importance degree of the target characteristic parameters, and adopting weighted calculation, wherein the weight is the preference setting of each characteristic parameter of the signal aiming at different combat tasks, radars with different purposes and different interference strategies;
Step 4, interference policy matching
According to the threat level queue sequence, processing is started by high priority, firstly, matching is carried out on a basic interference countermeasure identification library according to the characteristic parameters of threat signals of a first priority, and the base interference countermeasure identification library is matched preferentially according to interference frequencies, and secondly, the form, the interference type and the interference duration of interference signals are obtained;
step 5, updating basic interference countermeasure identification library
If the matching is not successful within the allowable range of the matching quantization error, inputting the characteristic parameters into a basic interference countermeasure identification library as a new training sample, and reclassifying;
Step 6, interference pattern setting
Combining the target threat degree and the limiting conditions of each interference device in the interference system, after the interference countermeasure identification library is successfully matched, converting the corresponding interference generation parameters, and then issuing the interference generation parameters to the corresponding interference devices;
Step 7, interference release
And each interference generating device generates corresponding interference signals in real time according to interference condition settings, wherein the interference conditions comprise interference types, interference intensity, interference frequency bands and interference opportunities.
2. The adaptive interference signal generation method based on interference policy guidance according to claim 1, wherein the extracting the characteristic parameters of the spatial target signal in step 2 comprises: azimuth pitch angle, signal strength, frequency, pulse duration, pulse repetition period, polarization characteristic measurement, signal form.
3. The adaptive interference signal generation method based on interference policy guidance according to claim 1, wherein the evaluation of the importance level of the target feature parameter in step 3 is obtained by an analytic hierarchy process based on expert scoring.
4. The adaptive interference signal generating method based on interference policy guidance according to claim 1, wherein in step 4, trend evaluation is continuously performed in a target signal scanning period, and countermeasures of the interference signal are determined.
5. The adaptive interference signal generation method based on interference policy guidance according to claim 1, wherein the updating step of the basic interference countermeasure identification library in step 5 is that intelligent learning is performed in combination with subsequent interference performance evaluation during internal field simulation or semi-physical simulation; in the field application, the credibility of the basic interference countermeasure identification library is ensured by manual intervention.
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| CN111157963A (en) * | 2020-01-31 | 2020-05-15 | 中国人民解放军32802部队 | Online evaluation method for interference effect of active phased array radar |
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