CN111835453B - Communication countermeasure process modeling method - Google Patents
Communication countermeasure process modeling method Download PDFInfo
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- CN111835453B CN111835453B CN202010615930.3A CN202010615930A CN111835453B CN 111835453 B CN111835453 B CN 111835453B CN 202010615930 A CN202010615930 A CN 202010615930A CN 111835453 B CN111835453 B CN 111835453B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
- H04K3/00—Jamming of communication; Counter-measures
- H04K3/40—Jamming having variable characteristics
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
- H04K3/00—Jamming of communication; Counter-measures
- H04K3/80—Jamming or countermeasure characterized by its function
Abstract
A communication countermeasure process modeling method is provided, which comprises the following steps: communication scout modeling; modeling communication interference; and (5) evaluating and modeling the interference effect. The modeling method can reduce the operation complexity of the reconnaissance model, improve the authenticity of the interference model, expand the application range of the effect evaluation model and carry out normalization processing on the interference effect.
Description
Technical Field
The invention relates to the technical field of communication countermeasure, in particular to a communication countermeasure process modeling method.
Background
Communication confrontation is increasingly playing a significant role in modern war. The communication countermeasure simulation platform is an important tool for researching the effect of the communication countermeasure. In the construction process of the communication countermeasure simulation platform, the modeling of the communication countermeasure process is a basic and important work.
The communication countermeasure process is generally divided into three parts, namely communication reconnaissance, communication interference and interference effect evaluation.
When modeling communication reconnaissance, the modeling is currently performed on a signal analysis level, such as extraction based on characteristic parameters, automatic identification of a modulation pattern, modulation and demodulation of a signal, and the like. The communication reconnaissance modeling based on signal analysis has high operation complexity, long operation time in a simulation platform and no real-time property. And different communication countermeasure equipment have different processing methods for signals, so the communication reconnaissance model based on signal analysis does not have universal applicability.
When modeling communication interference, a communication interference model based on an interference equation is established at present, and the model only studies the interference of a single interference station on a single target signal and simply takes an interference-to-signal ratio as an output of the model. In a real battlefield environment, an interference beam of a single interference station can cover a plurality of targets, so that interference is performed on a plurality of target signals, and the same interference target can be interfered by a plurality of interference stations. Meanwhile, the interference-signal ratio is simply taken as output without considering the alignment degree of the frequency, and the method has great difference with the actual effect.
In the interference effect evaluation modeling, currently, most of the interference effects of a single interference station on a single communication link are evaluated, and the influence of an interference pattern on the interference effects is not considered. In the complex electromagnetic environment of a real battlefield, a plurality of interference stations may generate interference effects on a single communication link, so that the interference effect evaluation of the single station lacks authenticity. In addition, most of the existing communication adopts a networking mode, and an interference effect evaluation model of a single communication link cannot reflect the interference effect on the whole communication network. Furthermore, the influence of the interference pattern on the interference effect is not reflected in the modeling.
Disclosure of Invention
Aiming at the defects of the current communication countermeasure process model, the invention provides a communication countermeasure process modeling method, which specifically comprises the following steps:
step 1: communication reconnaissance modeling
Step 1-1: the communication scouting model receives a scouting frequency band from the decision terminal, and the scouting frequency band is set as f 1 ～f 2 Then, screening out communication signals in the frequency band from all enemy communication signals as investigation target signals;
step 1-2: calculating the power of the reconnaissance target signal before reaching the reconnaissance receiver
Step 1-2-1: calculating the scout distance r D ：
Wherein (x) D ，y D ，z D ) To scout the device position coordinates, (x) 1 ，y 1 ，z 1 ) In order to detect the coordinates of the target signal transmitting radio station, the coordinate system is a three-dimensional rectangular coordinate system;
step 1-2-2: calculating the attenuation power L of the scout target signal in the scout channel D ：L D (dB)＝120+40lg r D (km)-20lg h T (m)·h RD (m), converting the dB value into a conventional power value, namely:
r D for scouting distances, h T For investigating the height of the target signal transmitting antenna, i.e. z 1 ，h RD For investigating the height of the antenna, i.e. z D ；
Step 1-2-3: calculating the power P of the front scout target signal of the scout receiver D ：
P TS For investigating the transmission power of the target signal, G T2 Side lobe gain, G, of the transmitting antenna for the scouting object signal D Gain for the scout antenna;
step 1-3: calculating search capture probability P of reconnaissance target signal 1
Setting the sensitivity of a search receiver in the reconnaissance equipment as k, and the power of a reconnaissance target signal reaching the search receiver as P D The scout equipment has n d The station search receiver is connected end to end, the search speed is v, and the search frequency range is f 1 ～f 2 And if the duration of the reconnaissance target signal is t, then:
when P is present D When < k, P 1 ＝0；
When P is present D When k is more than or equal to k, the following components are adopted:
if it is
Then P is 1 ＝1；
If it is
Then
Step 1-4: determining scout result output object
Step 1-4-1: screening out search capture probability P 1 The number of the reconnaissance target signals is n s ；
Step 1-4-2: calculating the output number m of scout results s ：m s ＝(1-λ)n s Wherein λ is the environment complexity of the input at initialization, wherein λ ∈ (0, 1);
step 1-4-3: determining a scout result output object: sorting the screening results of the step 1-4-1 from large to small according to the search capture probability, and taking the top m s Outputting the object as a scout result;
step 1-5: calculating the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver
The arrival of each reconnaissance result output object calculated in step 1-2Reconnaissance of the power P in front of the receiver D Its signal-to-noise ratio before the scout receiver is
P n The power of the environmental noise input when the communication reconnaissance model is initialized;
step 1-6: searching equipment error distribution variance sigma corresponding to each reconnaissance result output object 2
The equipment reconnaissance capability table describes the equipment error distribution variance of the specific communication counterscout equipment when the reconnaissance equipment analyzes the reconnaissance signals with different signal-to-noise ratios, and the variance is usually obtained through a large number of experiments; searching an equipment reconnaissance capability table through the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver to obtain the equipment error distribution variance sigma corresponding to each reconnaissance result output object 2 ；
Step 1-7: calculating scout results
Judging whether the output object of the reconnaissance result is a fixed-frequency signal or not, if so, executing the steps 1-7-1, 1-7-2, 1-7-5 and 1-7-6; otherwise, executing steps 1-7-3, 1-7-4, 1-7-5 and 1-7-6;
step 1-7-1: reconnaissance result f of calculating center frequency δ ：
The invention assumes that the error of the center frequency reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the error distribution of the equipment 2 (ii) a Calling the error normal distribution function of the frequency scout result to obtain a random value which is the frequency error delta f (ii) a Frequency scout result f δ ＝δ f + f, f is the real center frequency of the output object of the scout result;
step 1-7-2: computational bandwidth scout result B δ ：
Assuming that the error of the bandwidth scout result is subject to normal distribution, the mean value is 0, and the variance is the variance sigma of the equipment error distribution 2 (ii) a Calling an error normal distribution function of the bandwidth scout result to obtain a random value which is the bandwidth error delta B (ii) a Bandwidth scout result B δ ＝δ B + B, B is the real bandwidth of the output object of the scout result;
step 1-7-3: calculating a frequency set scout result:
assuming that the frequency point number of the reconnaissance result of the frequency set obeys normal distribution, the average value is the frequency point number N of the actual frequency set of the reconnaissance result output object, and the variance is the equipment error distribution variance sigma 2 (ii) a Calling the frequency point normal distribution function to obtain a random value which is the frequency point number N' of the frequency set scouting result; let the correct number of frequency points in the frequency set scout result be n t In which
If N' is less than or equal to N, randomly extracting N from the actual frequency set of the reconnaissance result output object t The frequency points form a set as a frequency set scouting result;
if N' > N, randomly extracting N from the actual frequency set of the reconnaissance result output object t At one frequency point and then at two ends respectively
Forming a set by the frequency points as a scout result of the frequency set, wherein the continuation step is consistent with the step of the true frequency set of an output object of the scout result;
1-7-4: calculating jumping speed scout result V δ ：
Assuming that the error of the jumping speed reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the equipment error distribution 2 (ii) a Calling an error normal distribution function of the jumping speed reconnaissance result to obtain a random value which is the jumping speed error delta V (ii) a Jumping speed scout result V δ ＝δ V + V, V is the real jumping speed of the output object of the scout result;
1-7-5: calculating the credibility P of the reconnaissance result of the modulation pattern 2 ：
Assuming that the error of the modulation pattern reconnaissance result follows normal distribution, the mean value is 1, and the variance is
Calling the error normal distribution function of the modulation pattern reconnaissance result to obtain a random value which is the modulationError P of model reconnaissance result 2δ If, if
Then recalling the error normal distribution function of the modulation pattern scout result to generate a new random value to be assigned to P 2δ Up to P 2δ ∈[0，2](ii) a Modulation pattern reconnaissance result credibility P 2 ＝|1-P 2δ |；
1-7-6: calculating a modulation pattern scout result:
the modulation modes are supposed to be AM, FM, SSB, FSK, PSK, QAM, MSK and TCM, wherein the former 3 modes are analog modulation modes, and the latter 5 modes are digital modulation modes;
if the actual modulation pattern of the reconnaissance result output object is a digital modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 4 digital modulation patterns is
The probability of any one of the 3 analog modulation patterns is
If the actual modulation pattern of the reconnaissance result output object is a certain simulation modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 2 analog modulation patterns is
The probability of being any one of 5 digital modulation patterns is
Step 2: communication interference modeling
Step 2-1: screening interfering target links
The communication interference model receives the interference direction and the interference parameters of the decision end, wherein the interference parameters comprise interference center frequency f j0 Interference bandwidth B j Interference transmission power P Tj An interference pattern; screening enemy communication receivers in a beam coverage range by using the interference direction and the self interference beam width, and taking communication links of the receivers as interference target links;
step 2-2: calculating the interference frequency band coverage of each interference target link
Step 2-2-1: calculating the interference frequency band f j1 ～f j2 ：
Step 2-2-2: calculating the communication frequency band f of the interference target link 1 ′～f′ 2 ：
Wherein f' 0 The communication center frequency of the interference target link, and B' is the communication bandwidth of the interference target link;
step 2-2-3: calculating an effective interference frequency band: if f 1 ′＞f j2 Or f' 2 ＜f j1 If yes, the effective interference frequency band is 0; otherwise will f j1 ，f j2 ，f 1 ′，f′ 2 The effective interference frequency ranges are arranged in an ascending order, and the effective interference frequency ranges are the frequency ranges from the second frequency to the third frequency which are arranged in the ascending order;
step 2-2-4: calculating the interference frequency band coverage eta of the interference target link:
step 2-3: calculating interference power P at receiver of each interference target link Rj
Step 2-3-1: computing reception of interfering target linksInterference distance r between machine and interfering device j ：
(x j ，y j ，z j ) Is a location coordinate of the jamming device, (x' 2 ，y′ 2 ，z′ 2 ) Position coordinates of a receiver for the interfering target link; the coordinate system is a three-dimensional rectangular coordinate system;
step 2-3-2: calculating the interference loss power L of the interference signal j ，L j (dB)＝120+40lg r j (km)-20lg h Tj (m)·h′ R (m), converting the dB value into a conventional power value, namely:
h Tj for interfering with the interfering antenna height of the device, i.e. z j ，h′ R Antenna height of receiver to interfere with target link, i.e. z' 2 ；
Step 2-3-3: calculating interference power P at receiver of interfering target link Rj ：
P Tj For interfering with the transmitted power, G j Is an interfering antenna gain, G' R2 Antenna side lobe gain, L, of receiver for interfering with target link j An interference loss power for the interfering signal;
step 2-4: calculating communication power P 'at receiver of each interfering target link' RS
Step 2-4-1: calculating the distance r 'of the communication parties of the interference target link' S ：
(x′ 1 ，y′ 1 ，z′ 1 ) Is a transmitter station location coordinate of the interfering target link, (x' 2 ，y′ 2 ，x′ 2 ) Receiver position coordinates for the interfering target link; the coordinate system is a three-dimensional rectangular coordinate system;
step 2-4-2: calculating communication loss power L 'of interference target link' S ：L′ S (dB)＝120+40lg r S (km)-20lg h′ T (m)·h′ R (m), converting the dB value into a conventional power value, namely:
h′ T is the antenna height of the transmitter station with the interfering target link, i.e. z' 1 ，h′ R Antenna height of receiver interfering with target link, namely z' 2 ；
Step 2-4-3: calculating communication power P 'at receiver interfering with target link' RS ：
P′ TS Is the signal transmit power, G ', of the transmitting station interfering with the target link' T1 Is the transmit station antenna main lobe gain, G ', with interfering target link' R1 Antenna main lobe gain, L ', for a receiver interfering with a target link' S Communication loss power for the interfering target link;
step 2-5: calculating a corrected interference-to-signal ratio at the receiver of each interference target link: correcting the interference-to-signal ratio to
And step 3: interference effect assessment modeling
Step 3-1: determining an interference pattern factor beta of an interference target link corresponding to each interference station
Table 1 is an interference pattern factor table, the horizontal axis of the table represents the communication modulation pattern of the interference target link, the vertical axis represents the interference pattern of the interference station, and the numbers in the table are the interference pattern factors under the specific interference pattern and the specific communication modulation pattern; aiming at a certain interference station, comparing an interference pattern factor table by combining an interference pattern of the certain interference station with a communication modulation pattern of an interference target link to obtain an interference pattern factor beta of the interference target link;
TABLE 1 interference Pattern factor Table
| AM | FM | SSB | FSK | PSK | QAM | MSK | TCM | |
| Noise AM | 0.6 | 0.4 | 0.5 | 0.5 | 0.4 | 0.6 | 0.3 | 0.3 |
| Noise FM | 1 | 0.8 | 0.6 | 0.7 | 0.6 | 0.6 | 0.5 | 0.4 |
| Noise DSB | 0.8 | 0.6 | 0.8 | 0.6 | 0.5 | 0.6 | 0.4 | 0.3 |
Step 3-2: calculating the equivalent interference-to-signal ratio of each interference station to the interference target link
For a certain interference target link corresponding to a certain interference station, the corrected interference-to-signal ratio is
The interference pattern factor is beta, the equivalent interference-to-signal ratio of the interference station to the target communication link is
Step 3-3: calculating the accumulative equivalent interference-to-signal ratio of each interference target link
The accumulated equivalent interference-signal ratio of the interference target link is equal to the sum of the equivalent interference-signal ratios of all the interference devices;
step 3-4: calculating the accumulated equivalent signal-to-noise ratio SNR of each interference target link Equivalence of
Cumulative equivalent signal-to-noise ratio (SNR) of interfering target link Equivalence of Equal to the reciprocal of its cumulative equivalent interference-to-signal ratio;
step 3-5: calculating the normalized interference effect of each interference target link
Judging whether the communication modulation pattern of the interference target link is a digital signal, if so, executing the steps 3-5-1 and 3-5-2, otherwise, executing the step 3-5-3;
step 3-5-1: calculating the bit error rate of each interference target link: table 2 is a digital signal error rate table, a corresponding error rate calculation formula is selected according to the communication modulation mode of the interference target link and the demodulation mode of a receiver thereof, and then the accumulated equivalent signal-to-noise ratio SNR of the interference target link is used Equivalence of Calculating the bit error rate P e ；
TABLE 2 digital signal error rate table
Where r is the equivalent signal-to-noise ratio SNR Equivalence of The specific conversion relationship of the dB values is as follows: r 10lg (SNR) Equivalence ) (ii) a erfc is a mathematical complementary error function, and the calculation mode is tabulated;
step 3-5-2: calculating the normalized interference effect alpha of each interference target link: table 3 is a table of normalized interference effects of digital signals, where the first column of the table represents the bit error rate P of the interfering target link e The second column indicates the bit error rate P e Corresponding normalized interference effect alpha according to the bit error rate P of the interference target link e Looking up a table 3 to obtain a normalized interference effect alpha of the interference target link;
TABLE 3 normalized interference effect table for digital signal
| Bit error rate P e | Interference effect alpha |
| P e ＞10 -1 | 1 |
| 5×10 -2 ＜P e ≤10 -1 | 0.9 |
| 10 -2 ＜P e ≤5×10 -2 | 0.8 |
| 8×10 -3 ＜P e ≤10 -2 | 0.7 |
| 6×10 -3 ＜P e ≤8×10 -3 | 0.6 |
| 4×10 -3 ＜P e ≤6×10 -3 | 0.5 |
| 2×10 -3 ＜P e ≤4×10 -3 | 0.4 |
| 10 -3 ＜P e ≤2×10 -3 | 0.3 |
| 5×10 -4 ＜P e ≤10 -3 | 0.2 |
| 10 -4 ＜P e ≤5×10 -4 | 0.1 |
| P e ≤10 -4 | 0 |
Step 3-5-3: calculating the normalized interference effect alpha of each interference target link: table 4 is a table of normalized interference effects of analog signals, where the first column of the table represents the cumulative equivalent signal-to-noise ratio SNR of the interfering target link Equivalence of And the second column represents the cumulative equivalent signal-to-noise ratio SNR Equivalence of Corresponding normalized interference effect alpha according to the accumulated equivalent signal-to-noise ratio SNR of the interference target link Equivalence of Looking up a table 4 to obtain a normalized interference effect alpha of the interference target link;
TABLE 4 analog signal normalization interference effect table
Step 3-6: calculating the importance index xi of each interference target link in the interference target network
Let the interfering target network have n h An interference target link is arranged, and the importance index of the ith interference target link is xi i Then there is
Wherein mu Ti Indicating the number of receivers, mu, owned by the transmitting station interfering with the target link in the ith Ri Indicating the number of transmitting stations owned by the receiver of the ith interference target link;
step 3-7: calculating the interference effect of an interfering target network
Setting the interference effect of the ith interference target link as alpha i The significance index is xi i Then interfere with the interference effect of the target network
The modeling method provided by the invention can reduce the operation complexity of the reconnaissance model, improve the authenticity of the interference model, expand the application range of the effect evaluation model and perform normalization processing on the interference effect.
The communication reconnaissance model obtains a reconnaissance result with errors and the credibility thereof based on the equipment capability, and can avoid the complex calculation problem in the specific signal analysis process.
The communication interference model considers the frequency coverage of interference to a target signal on the basis of the original interference model based on an interference equation, and uses the corrected interference-to-signal ratio as output, so that the authenticity of the communication interference model can be improved.
An interference pattern factor is introduced into the interference effect evaluation model, and the influence of the interference pattern on the interference effect is quantified; giving normalized interference effect values for a single communication link and the whole communication network; the calculation of the interference effect also takes the interference generated by a plurality of stations on the same target into account, and the application range of the interference effect evaluation model is expanded.
Drawings
FIG. 1 is a diagram of a particular communication countermeasure process modeled using the present invention;
FIG. 2 is a block diagram of the steps of a communication scout model method of the present invention;
FIG. 3 is a block diagram of the communication interference model method steps of the present invention;
fig. 4 is a block diagram of the interference effect evaluation model method according to the present invention.
Detailed Description
Fig. 1 is a diagram of a communication countermeasure process in an embodiment. The decision-making terminal firstly distributes a reconnaissance frequency band to the reconnaissance equipment of each station, the reconnaissance equipment of each station reconnaissance the communication parameters of the enemy in the reconnaissance frequency band of the reconnaissance equipment, and returns a reconnaissance result to the decision-making terminal. And the decision terminal analyzes and processes the reconnaissance result sent by the reconnaissance equipment of each station to generate an interference scheme and distributes interference parameters to the interference equipment of each station. And the interference equipment of each station releases interference according to the interference parameters. And finally, evaluating the interference effect, and feeding back the evaluation result to the decision end to further adjust the reconnaissance task allocation and the interference scheme generation. The modeling steps of the communication countermeasure process are described in detail below to make the objects, technical means, and advantages of the present application more apparent.
Step 1: communication reconnaissance modeling
Step 1-1: the communication scouting model receives a scouting frequency band from a decision terminal, and the scouting frequency band is set as f 1 ～f 2 And then, the communication signal in the frequency band is screened out from all enemy communication signals to be used as a detection target signal.
Step 1-2: calculating the power of the reconnaissance target signal before reaching the reconnaissance receiver:
step 1-2-1: calculating the scout distance r D ：
Wherein (x) D ，y D ，z D ) To reconnaissance the device position coordinates, (x) 1 ，y 1 ，z 1 ) In order to detect the coordinates of the target signal transmitting station, the coordinate system is a three-dimensional rectangular coordinate system.
Step 1-2-2: calculating the attenuation power L of the scout target signal in the scout channel D ：L D (dB)＝120+40lg r D (km)-20lg h T (m)·h RD (m), from dB value to conventional power value, i.e.:
r D for scouting distances, h T For investigating the height of the target signal-transmitting antenna, i.e. z 1 ，h RD For investigating the height of the antenna, i.e. z D 。
Step 1-2-3: calculating the power P of the front scout target signal of the scout receiver D ：
P TS For investigating the transmission power of the target signal, G T2 Side lobe gain, G, of the transmitting antenna for the scouting object signal D To scout antenna gain.
Step 1-3: calculating search capture probability of reconnaissance target signalP 1 ：
Let the sensitivity of the search receiver in the reconnaissance equipment be k, and the power of the reconnaissance target signal reaching the search receiver (i.e. the power before reaching the reconnaissance receiver) be P D The scout equipment has n d The station search receiver is connected end to end, the search speed is v, and the search frequency range is f 1 ～f 2 (namely the scouting frequency band allocated by the decision terminal), if the duration of the scouting target signal is t, then:
when P is present D When < k, P 1 ＝0。
When P is D When k is more than or equal to k, the following components are adopted:
if it is
Then P is 1 ＝1。
If it is
Then
Step 1-4: determining a scout result output object:
step 1-4-1: screening out search capture probability P 1 The number of the reconnaissance target signals is n s 。
Step 1-4-2: calculating the output number m of scout results s ：m s ＝(1-λ)n s Where λ is the environment complexity of the input at initialization, where λ ∈ (0, 1).
Step 1-4-3: determining a scout result output object: sorting the screening results of the step 1-4-1 from large to small according to the search capture probability, and taking the top m s And outputting the object as a scout result.
Step 1-5: calculating the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver: the power P of each reconnaissance result output object before reaching the reconnaissance receiver is calculated in the step 1-2 D Its signal-to-noise ratio before the scout receiver is
P n And the power of the environmental noise input when the communication reconnaissance model is initialized.
Step 1-6: searching equipment error distribution variance sigma corresponding to each reconnaissance result output object 2 : the equipment scout capability table describes the equipment error distribution variance of a specific communication counterscout equipment when analyzing scout signals with different signal-to-noise ratios, and is usually obtained through a large number of experiments. Searching an equipment reconnaissance capability table through the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver to obtain the equipment error distribution variance sigma corresponding to each reconnaissance result output object 2 。
Step 1-7: calculating a reconnaissance result: judging whether the output object of the reconnaissance result is a fixed-frequency signal or not, if so, executing the steps 1-7-1, 1-7-2, 1-7-5 and 1-7-6; otherwise, executing the steps 1-7-3, 1-7-4, 1-7-5 and 1-7-6.
Step 1-7-1: reconnaissance result f of calculating center frequency δ ：
The invention assumes that the error of the center frequency reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the error distribution of the equipment 2 . Calling the error normal distribution function of the frequency scout result (i.e. generating a random value according to the normal distribution), and obtaining the random value which is the frequency error delta f . Frequency scout result f δ ＝δ f And f are the real center frequencies of the reconnaissance result output objects.
Step 1-7-2: computational bandwidth scout result B δ ：
The invention assumes that the error of the bandwidth reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the error distribution of the equipment 2 . Calling the error normal distribution function of the bandwidth scout result (i.e. generating a random value according to the normal distribution), and obtaining the random value which is the bandwidth error delta B . Bandwidth reconnaissance result B δ ＝δ B + B, B is the real bandwidth of the output object of the scout result.
Step 1-7-3: calculating a frequency set scout result:
the invention assumes the result of frequency set reconnaissanceThe frequency point number follows normal distribution, the average value is the frequency point number N of the actual frequency set of the reconnaissance result output object, and the variance is the equipment error distribution variance sigma 2 . And calling the frequency point normal distribution function (namely generating a random value according to the normal distribution), wherein the obtained random value is the frequency point number N' of the frequency set scouting result. Let the correct number of frequency points in the frequency set scout result be n t Wherein
If N' is less than or equal to N, randomly extracting N from the actual frequency set of the reconnaissance result output object t The frequency points form a set as a frequency set scouting result.
If N' > N, randomly extracting N from the actual frequency set of the reconnaissance result output object t At one frequency point and then at two ends respectively
And the frequency points form a set as a frequency set scouting result, wherein the continuation step is consistent with the step of the actual frequency set of the scout result output object.
1-7-4: calculating jumping speed scout result V δ ：
The invention assumes that the error of the jumping speed reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the error distribution of the equipment 2 . Calling an error normal distribution function of the jumping speed scouting result (namely generating a random value according to the normal distribution), wherein the obtained random value is the jumping speed error delta V . Jumping speed scout result V δ ＝δ V And V is the real jumping speed of the scout result output object.
1-7-5: calculating the credibility P of the reconnaissance result of the modulation pattern 2 ：
The invention assumes that the error of the modulation pattern reconnaissance result follows normal distribution, the mean value is 1, and the variance is
Calling the error normal distribution function of the modulation pattern scout result (i.e. generating according to the normal distribution function)A random value) obtained as an error P of the detection result of the modulation pattern 2δ If, if
Then recalling the error normal distribution function of the modulation pattern scout result to generate a new random value to be assigned to P 2δ Up to P 2δ ∈[0，2]. Modulation pattern reconnaissance result credibility P 2 ＝|1-P 2δ |。
1-7-6: calculating a modulation pattern scout result:
the invention assumes that the modulation modes comprise eight types, namely AM, FM, SSB, FSK, PSK, QAM, MSK and TCM, wherein the former 3 types are analog modulation modes, and the latter 5 types are digital modulation modes.
If the actual modulation pattern of the reconnaissance result output object is a digital modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 4 digital modulation patterns is
The probability of any one of the 3 analog modulation patterns is
If the actual modulation pattern of the reconnaissance result output object is a certain simulation modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 2 analog modulation patterns is
The probability of being any one of 5 digital modulation patterns is
And 2, step: communication interference modeling
Step 2-1: screening for interfering targetsAnd (3) marking a link: the communication interference model receives the interference direction and the interference parameters of the decision end, wherein the interference parameters comprise interference center frequency f j0 Interference bandwidth B j Interference transmission power P Tj And interference patterns. And screening out enemy communication receivers in the beam coverage range by utilizing the interference direction and the self interference beam width, and taking the communication links of the receivers as interference target links.
Step 2-2: calculating the interference frequency band coverage of each interference target link:
step 2-2-1: calculating the interference frequency band f j1 ～f j2 ：
Step 2-2-2: calculating the communication frequency band f of the interference target link 1 ′～f′ 2 ：
Wherein f' 0 Is the communication center frequency of the interfering target link, and B' is the communication bandwidth of the interfering target link.
Step 2-2-3: calculating an effective interference frequency band: if f 1 ′＞f j2 Or f' 2 ＜f j1 The effective interference band is 0. Otherwise will f j1 ，f j2 ，f 1 ′，f′ 2 And the effective interference frequency band is the frequency band between the second frequency and the third frequency after the ascending order.
Step 2-2-4: calculating the interference frequency band coverage eta of the interference target link:
step 2-3: calculating interference power P at receiver of each interference target link Rj ：
Step 2-3-1: between receiver and interfering device calculating an interfering target linkInterference distance r j ：
(x j ，y j ，z j ) Is a location coordinate of the jamming device, (x' 2 ，y′ 2 ，z′ 2 ) Is the location coordinates of the receiver of the interfering target link. The coordinate system is a three-dimensional rectangular coordinate system.
Step 2-3-2: calculating interference loss power L of interference signal j ，L j (dB)＝120+40lg r j (km)-20lg h Tj (m)·h′ R (m), converting the dB value into a conventional power value, namely:
h Tj as interfering antenna height of interfering devices, i.e. z j ，h′ R Antenna height of receiver to interfere with target link, z' 2 。
Step 2-3-3: calculating an interference power P at a receiver of an interfering target link Rj ：
P Tj For interfering with the transmission power, G j Is an interfering antenna gain, G' R2 Antenna side lobe gain, L, of receiver for interfering with target link j Power is lost for interference of the interfering signal.
Step 2-4: calculating communication power P 'at receiver of each interfering target link' RS ：
Step 2-4-1: calculating the distance r 'of the communication parties of the interference target link' S ：
(x′ 1 ，y′ 1 ，z′ 1 ) Is a transmitter station location coordinate of the interfering target link, (x' 2 ，y′ 2 ，z′ 2 ) Is the receiver position coordinates of the interfering target link. The coordinate system is a three-dimensional rectangular coordinate system.
Step 2-4-2: meterCalculating communication loss power L 'of interference target link' S ：L′ S (dB)＝120+40lg r S (km)-20lg h′ T (m)·h′ R (m), converting the dB value into a conventional power value, namely:
h′ T is the antenna height of the transmitter station with the interfering target link, i.e. z' 1 ，h′ R Antenna height of receiver interfering with target link, z' 2 。
Step 2-4-3: calculating communication power P 'at receiver interfering with target link' RS ：
P′ TS Is the signal transmit power, G ', of the transmitting station interfering with the target link' T1 Is the transmit station antenna main lobe gain, G ', with interfering target link' R1 Antenna main lobe gain, L ', for a receiver interfering with a target link' S Power is lost to the communication interfering with the target link.
Step 2-5: calculating a modified interference-to-signal ratio at the receiver of each interfering target link: correcting the interference-to-signal ratio to
And 3, step 3: interference effect assessment modeling
Step 3-1: determining an interference pattern factor beta of an interference target link corresponding to each interference station: table 1 is an interference pattern factor table, in which the horizontal axis of the table represents the communication modulation pattern of the interference target link, the vertical axis represents the interference pattern of the interfering station, and the numbers in the table are the interference pattern factor under the specific interference pattern and the specific communication modulation pattern. And aiming at a certain interference station, comparing the interference pattern factor table by combining the interference pattern of the certain interference station with the communication modulation pattern of the interference target link to obtain the interference pattern factor beta of the interference target link.
TABLE 1 interference Pattern factor Table
| AM | FM | SSB | FSK | PSK | QAM | MSK | TCM | |
| Noise AM | 0.6 | 0.4 | 0.5 | 0.5 | 0.4 | 0.6 | 0.3 | 0.3 |
| Noise FM | 1 | 0.8 | 0.6 | 0.7 | 0.6 | 0.6 | 0.5 | 0.4 |
| Noise DSB | 0.8 | 0.6 | 0.8 | 0.6 | 0.5 | 0.6 | 0.4 | 0.3 |
Step 3-2: calculating the equivalent interference-to-signal ratio of each interference station to the interference target link: for a certain interference target link corresponding to a certain interference station, the corrected interference-to-signal ratio is
The interference pattern factor is beta, the equivalent interference-to-signal ratio of the interference station to the target communication link is
Step 3-3: calculating the accumulative equivalent interference-to-signal ratio of each interference target link: the cumulative equivalent interference-to-signal ratio of the interfering target link is equal to the sum of the equivalent interference-to-signal ratios of all interfering devices.
Step 3-4: calculating the accumulated equivalent signal-to-noise ratio SNR of each interference target link Equivalence of : cumulative equivalent signal-to-noise ratio (SNR) of interfering target link Equivalence of Equal to the inverse of its cumulative equivalent interference-to-signal ratio.
Step 3-5: calculating the normalized interference effect of each interference target link: and judging whether the communication modulation pattern of the interference target link is a digital signal, if so, executing the steps 3-5-1 and 3-5-2, and otherwise, executing the step 3-5-3.
Step 3-5-1: meterCalculating the error rate of each interference target link: table 2 is a digital signal error rate table, a corresponding error rate calculation formula is selected according to the communication modulation mode of the interference target link and the demodulation mode of a receiver thereof, and then the accumulated equivalent signal-to-noise ratio SNR of the interference target link is used Equivalence of Calculating the bit error rate P e 。
TABLE 2 digital signal error rate table
Where r is the equivalent signal-to-noise ratio SNR Equivalence The specific conversion relationship of the dB values is as follows: r 10lg (SNR) Equivalence of ) (ii) a erfc is a mathematically complementary error function, and the calculation method can be found in a table.
Step 3-5-2: calculating the normalized interference effect alpha of each interference target link: table 3 is a table of normalized interference effects of digital signals, where the first column of the table represents the bit error rate P of the interfering target link e The second column indicates the bit error rate P e Corresponding normalized interference effect alpha according to the bit error rate P of the interference target link e And looking up the table 3 to obtain the normalized interference effect alpha of the interference target link.
TABLE 3 normalized interference effect table for digital signal
Step 3-5-3: calculating the normalized interference effect alpha of each interference target link: table 4 is a table of normalized interference effects of analog signals, where the first column of the table represents the cumulative equivalent signal-to-noise ratio SNR of the interfering target link Equivalence of And the second column represents the cumulative equivalent signal-to-noise ratio SNR Equivalence of Corresponding normalized interference effect alpha according to the accumulated equivalent signal-to-noise ratio SNR of the interference target link Equivalence of And looking up the table 4 to obtain the normalized interference effect alpha of the interference target link.
TABLE 4 analog signal normalization interference effect table
| Cumulative equivalent signal-to-noise ratio SNR Equivalence of | Interference effect alpha |
| SNR Equivalence of ≤0dB | 1 |
| 0dB＜SNR Equivalence of ≤2dB | 0.9 |
| 2dB＜SNR Equivalence of ≤4dB | 0.8 |
| 4dB＜SNR Equivalence of ≤6dB | 0.7 |
| 6dB＜SNR Equivalence of ≤8dB | 0.6 |
| 8dB＜SNR Equivalence ≤10dB | 0.5 |
| 10dB＜SNR Equivalence of ≤12dB | 0.4 |
| 12dB＜SNR Equivalence of ≤14dB | 0.3 |
| 14dB＜SNR Equivalence of ≤16dB | 0.2 |
| 16dB＜SNR Equivalence of ≤18dB | 0.1 |
| SNR Equivalence of ＞18dB | 0 |
Step 3-6: calculating an importance index xi of each interference target link in the interference target network: let the interfering target network have n h An interference target link is arranged, and the importance index of the ith interference target link is xi i Then there is
Wherein mu Ti Indicating the number of receivers, mu, owned by the transmitting station interfering with the target link in the ith Ri Indicating the number of transmitting stations owned by the receiver of the ith interfering target link.
Step 3-7: calculating the interference effect of the interference target network: setting the interference effect of the ith interference target link as alpha i (see tables 3 and 4), and the importance index is ξ i Then interference effect of interfering target network
The invention has been described in detail with reference to specific examples only, and is not to be construed as limited in any manner, as many variations and modifications are possible without departing from the spirit of the invention, and the scope of the invention is to be determined accordingly.
Claims (1)
1. A communication countermeasure process modeling method is characterized by specifically comprising the following steps:
step 1: communication reconnaissance modeling
Step 1-1: the communication scouting model receives a scouting frequency band from the decision terminal, and the scouting frequency band is set as f 1 ～f 2 Then, screening out communication signals in the frequency band from all enemy communication signals as investigation target signals;
step 1-2: calculating the power of the reconnaissance target signal before reaching the reconnaissance receiver
Step 1-2-1: calculating the scout distance r D ：
Wherein (x) D ，y D ，z D ) To reconnaissance the device position coordinates, (x) 1 ，y 1 ，z 1 ) In order to scout the coordinates of a target signal transmitting station, the coordinate system is a three-dimensional rectangular coordinate system;
step 1-2-2: calculating the attenuation power L of the scout target signal in the scout channel D ：L D (dB)＝120+40lg r D(km)-20lg h T (m)·h RD (m), converting the dB value into a conventional power value, namely:
r D for scouting distances, h T For investigating the height of the target signal transmitting antenna, i.e. z 1 ，h RD For investigating the height of the antenna, i.e. z D ；
Step 1-2-3: calculating the power P of the front scout target signal of the scout receiver D ：
P TS For investigating the transmission power of the target signal, G T2 Side lobe gain, G, of the transmitting antenna for the scouting object signal D Gain for the scout antenna;
step 1-3:calculating search capture probability P of reconnaissance target signal 1
Setting the sensitivity of a search receiver in the reconnaissance equipment as k, and the power of a reconnaissance target signal reaching the search receiver as P D The scout equipment has n d The station search receiver is connected end to end, the search speed is v, and the search frequency range is f 1 ～f 2 And if the duration of the reconnaissance target signal is t, then:
when P is present D When < k, P 1 ＝0；
When P is present D When k is more than or equal to k, the following components are adopted:
if it is
Then P is 1 ＝1；
If it is
Then
Step 1-4: determining scout result output object
Step 1-4-1: screening out search capture probability P 1 The number of the reconnaissance target signals is n s ；
Step 1-4-2: calculating the output number m of scout results s ：m s ＝(1-λ)n s Wherein λ is the environment complexity of the input at initialization, wherein λ ∈ (0, 1);
step 1-4-3: determining a scout result output object: sorting the screening results of the step 1-4-1 from large to small according to the search capture probability, and taking the top m s Outputting the object as a scout result;
step 1-5: calculating the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver
The power P of each reconnaissance result output object before reaching the reconnaissance receiver is calculated in the step 1-2 D Its signal-to-noise ratio before the scout receiver is
P n The power of the environmental noise input when the communication reconnaissance model is initialized;
step 1-6: searching equipment error distribution variance sigma corresponding to each reconnaissance result output object 2
The equipment reconnaissance capability table describes equipment error distribution variance of the specific communication counterscout equipment when the reconnaissance equipment analyzes the reconnaissance signals with different signal-to-noise ratios, and the equipment error distribution variance is obtained through a large number of experiments; searching an equipment reconnaissance capability table through the signal-to-noise ratio of each reconnaissance result output object in front of the reconnaissance receiver to obtain the equipment error distribution variance sigma corresponding to each reconnaissance result output object 2 ；
Step 1-7: calculating scout results
Judging whether the output object of the reconnaissance result is a fixed-frequency signal or not, if so, executing the steps 1-7-1, 1-7-2, 1-7-5 and 1-7-6; otherwise, executing steps 1-7-3, 1-7-4, 1-7-5 and 1-7-6;
step 1-7-1: reconnaissance result f for calculating center frequency δ ：
Assuming that the error of the center frequency scout result is subject to normal distribution, the mean value is 0, and the variance is the variance sigma of the equipment error distribution 2 (ii) a Calling the error normal distribution function of the frequency scout result to obtain a random value which is the frequency error delta f (ii) a Frequency scout result f δ ＝δ f + f, f is the real center frequency of the output object of the scout result;
step 1-7-2: computational bandwidth scout result B δ ：
Assuming that the error of the bandwidth scout result is subject to normal distribution, the mean value is 0, and the variance is the variance sigma of the equipment error distribution 2 (ii) a Calling an error normal distribution function of the bandwidth scout result to obtain a random value which is the bandwidth error delta B (ii) a Bandwidth scout result B δ ＝δ B + B, B is the real bandwidth of the output object of the scout result;
step 1-7-3: calculating a frequency set scout result:
assuming that the frequency point number of the reconnaissance result of the frequency set obeys normal distribution, and the average value is the reconnaissance resultThe frequency point number N of the real frequency set of the fruit output object, the variance is the variance sigma of the equipment error distribution 2 (ii) a Calling a frequency point normal distribution function, namely generating a random value according to the normal distribution, wherein the obtained random value is the frequency point number N' of the frequency set scouting result; let the correct number of frequency points in the frequency set scout result be n t Wherein
If N' is less than or equal to N, randomly extracting N from the actual frequency set of the reconnaissance result output object t The frequency points form a set as a frequency set scouting result;
if N' > N, randomly extracting N from the actual frequency set of the reconnaissance result output object t At one frequency point and then at two ends respectively
The frequency points form a set as a frequency set scouting result, wherein the continuation step is consistent with the step of the actual frequency set of an output object of the scouting result;
1-7-4: calculating jumping speed scout result V δ ：
Assuming that the error of the jumping speed reconnaissance result follows normal distribution, the mean value is 0, and the variance is the variance sigma of the error distribution of equipment 2 (ii) a Calling an error normal distribution function of the jumping speed reconnaissance result to obtain a random value which is the jumping speed error delta V (ii) a Jumping speed scout result V δ ＝δ V + V, V is the real jumping speed of the output object of the scout result;
1-7-5: calculating the credibility P of the reconnaissance result of the modulation pattern 2 ：
Assuming that the error of the modulation pattern reconnaissance result follows normal distribution, the mean value is 1, and the variance is
Calling an error normal distribution function of the modulation pattern scouting result to obtain a random value which is the error P of the modulation pattern scouting result 2δ If, if
Then recalling the error normal distribution function of the modulation pattern scout result to generate a new random value to be assigned to P 2δ Up to P 2δ ∈[0，2](ii) a Modulation pattern reconnaissance result credibility P 2 ＝|1-P 2δ |；
1-7-6: calculating a modulation pattern scout result:
the modulation modes are assumed to be eight types, namely AM, FM, SSB, FSK, PSK, QAM, MSK and TCM, wherein the former 3 types are analog modulation modes, and the latter 5 types are digital modulation modes;
if the actual modulation pattern of the reconnaissance result output object is a digital modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 4 digital modulation patterns is
The probability of any one of the 3 analog modulation patterns is
If the actual modulation pattern of the reconnaissance result output object is a certain simulation modulation pattern, the probability that the reconnaissance result is the actual modulation pattern is P 2 The probability of any one of the other 2 analog modulation patterns is
The probability of being any one of 5 digital modulation patterns is
Step 2: communication interference modeling
Step 2-1: screening interfering target links
Communication interference model receiving interference of decision terminalDirection and interference parameters including interference center frequency f j0 Interference bandwidth B j Interference transmission power P Tj An interference pattern; screening enemy communication receivers in a beam coverage range by using the interference direction and the self interference beam width, and taking communication links of the receivers as interference target links;
step 2-2: calculating the interference frequency band coverage of each interference target link
Step 2-2-1: calculating the interference frequency band f j1 ～f j2 ：
Step 2-2-2: calculating the communication frequency band f of the interference target link 1 ′～f′ 2 ：
Wherein f' 0 Is the communication center frequency of the interference target link, and B' is the communication bandwidth of the interference target link;
step 2-2-3: calculating an effective interference frequency band: if f 1 ′＞f j2 Or f' 2 ＜f j1 If yes, the effective interference frequency band is 0; otherwise will f j1 ，f j2 ，f 1 ′，f′ 2 The effective interference frequency band is the frequency band between the second frequency and the third frequency after the ascending order;
step 2-2-4: calculating the interference frequency band coverage eta of the interference target link:
step 2-3: calculating interference power P at receiver of each interference target link Rj
Step 2-3-1: calculating an interference distance r between a receiver of an interfering target link and an interfering device j ：
(x j ，y j ，z j ) Is the position coordinate of the interfering device (x' 2 ，y′ 2 ，z′ 2 ) Position coordinates of a receiver that is an interfering target link; the coordinate system is a three-dimensional rectangular coordinate system;
step 2-3-2: calculating interference loss power L of interference signal j ，L j (dB)＝120+40lg r j (km)-20lg h Tj (m)·h′ R (m), converting the dB value into a conventional power value, namely:
h Tj for interfering with the interfering antenna height of the device, i.e. z j ，h′ R Antenna height, i.e., z ', of receiver to interfere with target link' 2 ；
Step 2-3-3: calculating interference power P at receiver of interfering target link Rj ：
P Tj For interfering with the transmitted power, G j Is an interfering antenna gain, G' R2 Antenna side lobe gain, L, of receiver for interfering with target link j An interference loss power for the interfering signal;
step 2-4: calculating communication power P 'at receiver of each interfering target link' RS
Step 2-4-1: calculating the distance r 'of the communication parties interfering the target link' S ：
(x′ 1 ，y′ 1 ，z′ 1 ) Is a transmitter station location coordinate of the interfering target link, (x' 2 ，y′ 2 ，z′ 2 ) Receiver position coordinates for the interfering target link; the coordinate system is a three-dimensional rectangular coordinate system;
step 2-4-2: calculating communication loss power L 'of interference target link' S ：
The dB value is converted into a conventional power value, namely:
h′ T is the antenna height of the transmitter station with the interfering target link, i.e. z' 1 ，h′ R Antenna height of receiver interfering with target link, i.e. z' 2 ；
Step 2-4-3: calculating communication power P 'at receiver interfering with target link' RS ：
P′ TS Is the signal transmit power, G ', of the transmitting station interfering with the target link' T1 Is the transmit station antenna main lobe gain, G ', with interfering target link' R1 Antenna main lobe gain, L ', for a receiver interfering with a target link' S Communication loss power for the interfering target link;
step 2-5: calculating a modified interference-to-signal ratio at the receiver of each interfering target link: correcting the interference-to-signal ratio to
And 3, step 3: interference effect assessment modeling
Step 3-1: determining an interference pattern factor beta of an interference target link corresponding to each interference station
Table 1 is an interference pattern factor table, the horizontal axis of the table represents the communication modulation pattern of the interference target link, the vertical axis represents the interference pattern of the interference station, and the numbers in the table are the interference pattern factors under the specific interference pattern and the specific communication modulation pattern; aiming at a certain interference station, comparing an interference pattern factor table by combining an interference pattern of the certain interference station with a communication modulation pattern of an interference target link to obtain an interference pattern factor beta of the interference target link;
TABLE 1 interference Pattern factor Table
Step 3-2: calculating the equivalent interference-to-signal ratio of each interference station to the interference target link
For a certain interference target link corresponding to a certain interference station, the corrected interference-to-signal ratio is
The interference pattern factor is beta, the equivalent interference-to-signal ratio of the interference station to the interference target link is
Step 3-3: calculating the accumulative equivalent interference-to-signal ratio of each interference target link
The accumulated equivalent interference-signal ratio of the interference target link is equal to the sum of the equivalent interference-signal ratios of all the interference devices;
step 3-4: calculating the accumulated equivalent signal-to-noise ratio SNR of each interference target link Equivalence of
Cumulative equivalent signal-to-noise ratio (SNR) of interfering target link Equivalence of Equal to the reciprocal of its cumulative equivalent interference-to-signal ratio;
step 3-5: calculating the normalized interference effect of each interference target link
Judging whether the communication modulation pattern of the interference target link is a digital signal, if so, executing the steps 3-5-1 and 3-5-2, otherwise, executing the step 3-5-3;
step 3-5-1: calculating the bit error rate of each interference target link: table 2 is a digital signal error rate table, a corresponding error rate calculation formula is selected according to the communication modulation mode of the interference target link and the demodulation mode of a receiver thereof, and then the accumulated equivalent signal-to-noise ratio SNR of the interference target link is used Equivalence of Calculating the bit error rate P e ；
TABLE 2 digital signal error rate table
Where r is the equivalent signal-to-noise ratio SNR Equivalence of The specific conversion relationship of the dB values is as follows: r 10lg (SNR) Equivalence of ) (ii) a erfc is a mathematical complementary error function, and the calculation mode is tabulated;
step 3-5-2: calculating the normalized interference effect alpha of each interference target link: table 3 is a table of normalized interference effects of digital signals, where the first column of the table represents the bit error rate P of the interfering target link e The second column indicates the bit error rate P e Corresponding normalized interference effect alpha according to the bit error rate P of the interference target link e Looking up a table 3 to obtain a normalized interference effect alpha of the interference target link;
TABLE 3 normalized interference effect table for digital signal
Step 3-5-3: calculating the normalized interference effect alpha of each interference target link: table 4 is a table of normalized interference effects of analog signals, where the first column of the table represents the cumulative equivalent signal-to-noise ratio SNR of the interfering target link Equivalence of And the second column represents the cumulative equivalent signal-to-noise ratio SNR Equivalence of Corresponding normalized interference effect alpha according to the accumulated equivalent signal-to-noise ratio SNR of the interference target link Equivalence of Looking up a table 4 to obtain a normalized interference effect alpha of the interference target link;
TABLE 4 analog signal normalization interference effect table
Step 3-6: calculating the importance index xi of each interference target link in the interference target network
Let the interfering target network have n h An interference target link is arranged, and the importance index of the ith interference target link is xi i Then there is
Wherein mu Ti Indicating the number of receivers, mu, owned by the transmitting station interfering with the target link in the ith Ri Indicating the number of transmitting stations owned by the receiver of the ith interference target link; step 3-7: calculating the interference effect of an interfering target network
Let the interference effect of the ith interference target link be alpha i The significance index is xi i Then interfere with the interference effect of the target network
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| CN107315891A (en) * | 2017-07-17 | 2017-11-03 | 电子科技大学 | Airborne communication interference course line modeling and jamming Efficiency Evaluation method based on radiation source |
| CN109302262A (en) * | 2018-09-27 | 2019-02-01 | 电子科技大学 | A kind of communication anti-interference method determining Gradient Reinforcement Learning based on depth |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107315891A (en) * | 2017-07-17 | 2017-11-03 | 电子科技大学 | Airborne communication interference course line modeling and jamming Efficiency Evaluation method based on radiation source |
| CN109302262A (en) * | 2018-09-27 | 2019-02-01 | 电子科技大学 | A kind of communication anti-interference method determining Gradient Reinforcement Learning based on depth |
Non-Patent Citations (1)
| Title |
|---|
| 电子对抗环境下的目标探测模型研究;周林等;《弹箭与制导学报》;20010330(第01期);全文 * |
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