Communication interference optimization configuration method and system based on double-layer stochastic programming and medium

Abstract

The application provides a communication interference optimization configuration method and system based on double-layer random programming and a medium, and comprises the following steps: based on the combat region range, the upper limit of the number of distributed communication interference systems, the required communication interference suppression time length, the effective suppression coefficient, the technical parameters of the air defense wireless communication system and the distributed copper wire interference system, a target function value is calculated by using the random programming, and the optimal position of the wireless communication receiver is obtained based on the genetic algorithm of the random programming. The application obtains the effective determination of the distributed communication receiver based on the random programming algorithm, and ensures the effectiveness of the communication countermeasure reconnaissance in the low-power environment.

Description

Technical Field

[0001] This invention relates to the field of communications, and specifically to a communication interference optimization configuration method, system, and medium based on two-layer stochastic programming. Background Technology

[0002] Distributed jamming is a type of electronic jamming method used to cover specific targets. Distributed jamming can provide flexible jamming methods according to signal states, and its distributed jamming effectiveness against any type of jamming signal improves the basic level of distributed jamming. In distributed jamming, the number of jammers is limited, increasing the difficulty of coordinated operation and requiring certain survivability. Distributed communication jamming systems are typically used when air assault formations are about to enter the end of their penetration route and the target's strike area. Before deployment, the location of the main wireless transmitter and possibly the approximate location of some receivers are generally known.

[0003] In existing communication processes between transceivers, the transmitter and receiver are often relatively separated. Communication countermeasures reconnaissance can typically only detect the approximate location of the transmitter, not the precise location of the receiver. This characteristic makes it difficult for the party carrying out communication jamming to implement "tracking and targeting jamming" on the receiver. For high-power communication jamming systems, "wide-beam targeting of the transmitter" is often used to address this problem. However, this approach is clearly unsuitable for low-power distributed communication jamming systems. Therefore, it is urgent to re-analyze and re-examine the application scenarios and effectiveness evaluation models of distributed communication jamming systems. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a communication interference optimization configuration method, system, and medium based on two-layer stochastic programming. The optimal solution of the distributed communication interference system optimization configuration model is obtained by using a genetic algorithm based on stochastic programming, which ensures the effective determination of the location of the communication receiver and guarantees countermeasure reconnaissance during communication.

[0005] The first aspect of this invention discloses a communication interference optimization configuration method based on two-layer stochastic programming, comprising the following steps:

[0006] Step S1: Input the operational area's range (width, length), the maximum number N of distributed communication jamming systems, the required suppression duration T, and the effective suppression coefficient K. j Parameters of air defense wireless communication system and distributed communication jamming system, genetic generation number M, initial population size N ind Crossover probability p c and the mutation probability p m Raw calculation data;

[0007] Step S2: generating an initial population of distributed jamming system configuration positions and initial positions (x r0 ,y r0 ) of air defense wireless communication receivers based on the original calculation data;

[0008] Step S3: calculating the objective function value f(m) in the communication system optimization model according to the generated initial population and initial positions (x r0 ,y r0 ), wherein the communication system optimization model is set as:

[0009]

[0010]

[0011] wherein n m is the number of the mth configuration scheme of the distributed communication jamming system, N is the upper limit of the number of the distributed communication jamming system, is the probability of achieving effective suppression of wireless communication in the T period by the mth configuration scheme, a is the confidence probability of achieving the minimum combat requirement, width is the front width of the combat region, length is the depth length of the combat region, the communication receiver position (x rm ,y rm ), and the effective suppression probability P m ; J rt is the interference signal power received by the communication receiver; and S rt is the communication transmitter signal power received by the communication receiver.

[0012] Step S4: calculating the fitness according to the objective function value, and performing selection, crossover and mutation operations on the population to obtain a new generation of population;

[0013] Step S5: adjusting the position (x rm ,y rm ) of the air defense wireless communication receiver, and then repeating the steps S3-S4 until m>M.

[0014] Step S6: taking the population corresponding to the minimum objective function value f min (m) in the solving process as the best configuration scheme.

[0015] According to the method of the first aspect of the present application, the initial position (x r0 ,y r0 ) of the air defense wireless communication receiver in the step S2 is randomly selected within the length and width range of the combat region.

[0016] According to the method of the first aspect of the present application, the effective suppression probability P mThe determination method is as follows:

[0017] Let the position of the communication transmitter s be (x s ,y s The location of the communication receiver that initiates communication with it at time t is (x rt ,y rt If the m-th configuration scheme is used to implement distributed interference, the configuration locations of each distributed communication interference system are as follows: Where m i Let i be the configuration location of the i-th distributed communication jamming system. Then, the interference-to-signal ratio formed by the receiver at time t is:

[0018]

[0019] In the formula, J rt The power of the interference signal received by the communication receiver; S rt The signal power received by the communication receiver from the communication transmitter; P j G j P is the equivalent power of the jamming signal emitted by the distributed communication jamming system. t G t The equivalent power of the communication signal transmitted by the communication transmitter; γ j For the interference polarization loss of the distributed communication interference system; B rj R is the bandwidth ratio of the communication signal to the interference signal. rt q represents the distance between the receiver and transmitter in a communication system. rt Let be the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; q represents the antenna gain of the receiver in the direction of the transmitter; ri (θ) represents the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; Let q be the signal transmission loss of the i-th distributed communication interference system; rt Let be the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; R represents the antenna gain of the receiver in the direction of the transmitter; rt R is the distance between the receiver and the transmitter. ri Let be the distance between the communication receiver and the i-th distributed communication jamming system;

[0020] According to the analysis results of equation (1), in order for the wireless communication link to be effectively cut off at time t, the interference-to-signal ratio at the receiver end of the communication receiver must be greater than or equal to the effective suppression coefficient K. j ,Right now:

[0021]

[0022] The effective suppression probability P of implementing the configuration according to the m-th configuration scheme during time period T. m The calculation model is as follows:

[0023]

[0024] In the formula, rect(x) is the unit step function; T is the simulation duration.

[0025] According to the method of the first aspect of the present invention, the location (x) of the communication receiver in step S3 rm ,y rm Set to:

[0026] Location of the air defense system wireless communication receiver (x) rm ,y rm The calculation model is as follows:

[0027]

[0028] In the formula, (x r0 ,y r0 ) represents the initial position of the wireless communication receiver of the air defense system, which is usually randomly selected within the length and width range of the combat area; ΔR represents the positioning error; The angle of the current position relative to the center is rand(0,2π).

[0029] According to the method of the first aspect of the present invention, step S3 further includes:

[0030] Step S31: Set the initial interference time t = 0, and the number of effective suppression attempts N. j =0;

[0031] Step S32: Calculation Does it hold true? If it does, then N j =N j If t = t + 1 and t = t + 1, otherwise only execute t = t + 1;

[0032] Step S33: Continue executing step S32 until t > T, then calculate... If the condition is met, then the number n of distributed communication interference systems can be calculated based on the current population. m This involves extracting the number of populations whose coordinates are not in (-1, -1) and calculating the objective function value accordingly. If the condition is not met, a penalty mechanism is activated, and the objective function value is determined to be f(m) = 1.

[0033] According to the method of the first aspect of the present invention, the distributed communication interference system optimization configuration model in step S3 can be defined as:

[0034]

[0035]

[0036] According to the method of the first aspect of the present invention, the determination condition for the effective suppression probability is set as follows: in the battlefield situation, all wireless communication links in the combat area adopt omnidirectional antennas and implement communication in a unified frequency band, and the distributed communication jamming system can effectively target the working frequency band of wireless communication.

[0037] The second aspect of the present invention discloses a communication interference optimization configuration system based on two-level stochastic programming, including a computer device for executing the steps of the communication interference optimization configuration method based on two-level stochastic programming described in the first aspect.

[0038] The third aspect of the present invention discloses a computer-readable storage medium storing a computer program to implement the communication interference optimization configuration method based on two-level stochastic programming described in the first aspect.

[0039] In summary, the proposed solution of this invention has the following technical effects: by setting the effective suppression probability, the configuration position of the communication jamming system is obtained; by using a genetic algorithm based on stochastic programming to obtain the optimal solution of the distributed communication jamming system optimization configuration model, the effective determination of the communication receiver position in a low-power distributed communication jamming system is guaranteed. Attached Figure Description

[0040] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is a flowchart of the communication interference optimization configuration method based on two-layer stochastic programming of the present invention;

[0042] Figures 2a-2j This is a schematic diagram of the simulation calculation results of an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] like Figure 1 As shown, this invention provides a communication interference optimization configuration method based on two-layer stochastic programming, comprising the following steps:

[0045] Step S1: Input the operational area's range (width, length), the maximum number N of distributed communication jamming systems, the required suppression duration T, and the effective suppression coefficient K. j Parameters of air defense wireless communication system and distributed communication jamming system, genetic generation number M, initial population size N ind Crossover probability p c and the mutation probability p m Raw calculation data;

[0046] Step S2: Based on the original calculation data, generate the initial population for the distributed jamming system configuration location and the initial location (x) of the air defense wireless communication receiver. r0 ,y r0 );

[0047] Step S3: Based on the generated initial population and initial position (x) r0 ,y r0 The objective function value f(m) in the communication system optimization model is calculated using stochastic programming. The communication system optimization model is set as follows:

[0048]

[0049]

[0050] In the formula, n m Here, N represents the number of distributed communication jamming systems in configuration scheme m, and N is the upper limit for the number of distributed communication jamming systems. Let m be the probability that configuration scheme m will effectively suppress wireless communication within time period T, 'a' be the confidence probability of achieving the minimum operational requirements, 'width' be the frontal width of the operational area, 'length' be the depth of the operational area, and 'x' be the location of the communication receiver. rm ,y rm Effective suppression probability P m ;

[0051] Step S4: Calculate the fitness based on the objective function value, and perform selection, crossover, and mutation operations on the population to obtain a new generation of population;

[0052] Step S5: Adjust the position of the air defense wireless communication receiver (x) rm ,y rm Then repeat steps S3 to S4 until m > M;

[0053] Step S6: Calculate the minimum objective function value f during the solution process. min The population corresponding to (m) is taken as the optimal configuration scheme.

[0054] For the effective suppression probability P m To simplify calculations, the following assumptions are made regarding the battlefield situation: ① It is assumed that all wireless communication links within the combat area use omnidirectional antennas and communicate within a unified frequency band; ② It is assumed that distributed communication jamming systems can effectively target the operating frequency band of wireless communication.

[0055] Let the position of the communication transmitter s be (x s ,y s The location of the communication receiver that initiates communication with it at time t is (x rt ,y rt If the m-th configuration scheme is used to implement distributed interference, the configuration locations of each distributed communication interference system are as follows: Where m i Let i be the configuration location of the i-th distributed communication jamming system. Then, the interference-to-signal ratio formed by the receiver at time t is:

[0056]

[0057] In the formula, q ri (θ) represents the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; Let q be the signal transmission loss of the i-th distributed communication interference system; rt Let be the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; R represents the antenna gain of the receiver in the direction of the transmitter; rt R is the distance between the receiver and the transmitter. ri Let be the distance between the communication receiver and the i-th distributed communication jamming system.

[0058] According to the analysis results of equation (2), in order for the wireless communication link to be effectively cut off at time t, the interference-to-signal ratio at the receiver end of the communication receiver must be greater than or equal to the effective suppression coefficient K. j ,Right now:

[0059]

[0060] To effectively ensure the air safety of friendly air strike formations at the end of their penetration route and in the target strike area, it is necessary to guarantee comprehensive suppression of air defense wireless communication links within the operational area during time period T, i.e., the effective suppression probability P. m This is guaranteed to be above a certain confidence probability. Since the receivers engaging in wireless communication with transmitter s change dynamically at different times within time period T, the effective suppression probability P under configuration scheme m within time period T is... m The calculation model is as follows:

[0061]

[0062] In the formula, rect(x) is the unit step function; T is the simulation duration.

[0063] For the location of the communication receiver (x) rm ,y rm The determination of the position of the distributed communication jammer (x) is crucial. Besides effective frequency alignment and comprehensive energy suppression, the effectiveness of distributed communication jamming is significantly influenced by the distance between the jammer and the receiver, as well as the angle formed between the receiver, transmitter, and distributed jammer. Therefore, to ensure the calculation model closely reflects actual combat, the following model of the receiver's position is constructed: ① Most of the systems targeted are mobile air defense systems, resulting in the position of the air defense wireless communication system changing dynamically over a period of time; ② During combat, the side conducting the suppression operation can usually determine the probabilistic position of the air defense communication system through intelligence support or reconnaissance. Based on this, the position (x) of the air defense system's wireless communication receiver is determined. rm ,y rm The calculation model should be:

[0064]

[0065] In the formula, (x r0 ,y r0 ) represents the initial position of the wireless communication receiver of the air defense system, which is usually randomly selected within the length and width range of the combat area; ΔR represents the positioning error; This is the angle of the current position relative to the center, usually rand(0,2π).

[0066] Based on the above analysis, the optimal configuration model for a distributed communication interference system can be defined as follows:

[0067]

[0068]

[0069] According to equation (6), the optimal configuration problem of a distributed communication interference system belongs to a nonlinear stochastic programming problem. Therefore, the calculation of this type of problem model can be performed using a "genetic algorithm based on stochastic programming". The specific solution process is as follows:

[0070] Step 1: Input the operational area's width, length, the maximum number of distributed communication jamming systems N, the required suppression duration T, and the effective suppression coefficient K. j Technical parameters of air defense wireless communication systems and distributed communication jamming systems, genetic generation number M, and initial population size N. ind Crossover probability p c and the mutation probability p m Original calculation data;

[0071] Step 2 generates the initial population for the distributed jamming system configuration location and the initial location (x) of the air defense wireless communication receiver. r0 ,y r0 );

[0072] Step 3: Based on the generated initial population and initial location (x) r0 ,y r0 The objective function value f(m) is calculated using stochastic programming.

[0073] Step 3.1 Set the initial interference time t = 0, and the number of effective suppression attempts N. j =0;

[0074] Step 3.2 Calculation Does it hold true? If it does, then N j =N j If t = t + 1 and t = t + 1, otherwise only execute t = t + 1;

[0075] Step 3.3 Continue executing step 3.2 until t > T, then calculate. If the condition is met, then the number n of distributed communication interference systems can be calculated based on the current population. m This involves extracting the number of populations whose coordinates are not in (-1, -1) and calculating the objective function value accordingly. If the condition is not met, a penalty mechanism is activated, and the objective function value is determined to be f(m) = 1.

[0076] Step 4: Calculate the fitness based on the objective function value, and perform selection, crossover, and mutation operations on the population to obtain a new generation of population;

[0077] Step 5: Adjust the position (x) of the air defense wireless communication receiver according to formula (5). rm ,y rm Then repeat steps 3 to 4 until m > M;

[0078] Step 6 will calculate the minimum objective function value f during the solution process. min The population corresponding to (m) is taken as the optimal configuration scheme.

[0079] Simulation tests were conducted using the above method. It was assumed that the area from which the air defense system carried out its mobile air defense mission was (20km, 20km), and the location of the main wireless transmitter of the air defense system was known, denoted as (x...). s ,y s The air defense system's wireless communication radio operates in the frequency band of 48.98MHz to 49.02MHz. The transmitter's signal transmission power is 10W, and the receiver's instantaneous bandwidth is 10KHz. Both the transmitter and receiver use omnidirectional antennas with a gain of 10dB and a height of 4m. The distributed communication jamming system has an interference power of 8W, an interference bandwidth of 48MHz to 50MHz, uses an omnidirectional antenna with a gain of 10dB, and has a continuous operating time of 50 minutes. The maximum number of systems is 200. The genetic algorithm has an initial population size of 50, a crossover probability of 0.8, and a mutation probability of 0.2. The system is required to maintain continuous suppression for up to 20 minutes.

[0080] Simulation 1: Under the condition that the location of the wireless communication receiver cannot be effectively determined, and with a confidence probability α = 0.8, the interference effect is simulated for five scenarios: the wireless communication transmitter is located at the four corners and the center of the operational area. The simulation results are as follows: Figures 2a-2e As shown. Among them Figure 2a The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the lower left corner and the receiver is not measured. Figure 2b The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the upper left corner and the receiver has not been measured. Figure 2c The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the upper right corner and the receiver has not been measured. Figure 2d The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the lower right corner and the receiver is not measured. Figure 2e The diagram shows the optimized configuration result of distributed interference when the main transmitter is in the middle and the receiver is not measured.

[0081] Simulation 2: Under the condition of effective location determination of the wireless communication receiver (error ΔR = 1000m) and confidence probability a = 0.8, the interference effect was simulated for five locations of the wireless communication transmitter, including the four corners and the center of the combat area. The simulation results are as follows. Figure 2f , Figure 2g , Figure 2h , Figure 2i , Figure 2j As shown. Figure 2f The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the lower left corner and the receiver has been measured. Figure 2gThe diagram shows the optimized distributed interference configuration when the primary transmitter is located in the upper left corner and the receiver has been measured. Figure 2h With the main transmitter located in the upper right corner and the receiver already measured, this is the result of the distributed interference optimization configuration. Figure 2i The diagram shows the optimized distributed interference configuration when the primary transmitter is located in the lower right corner and the receiver has been measured. Figure 2j The diagram shows the optimized configuration result of distributed interference when the main transmitter is in the middle and the receiver has been measured.

[0082] Based on the above simulation analysis, the following conclusions can be drawn:

[0083] (1) The optimal configuration result of the distributed communication jamming system has a “biased” characteristic. From the results of Simulation 1 and Simulation 2, when implementing distributed communication jamming, regardless of whether the location of the communication receiver is determined in advance, the optimal configuration scheme shows that most jammers are distributed at symmetrical angles far away from the main communication transmitter, i.e., “biased characteristic”, except when the main communication transmitter is in the center of the combat area.

[0084] (2) Fewer distributed communication jamming systems are needed when the communication receiver is located in one of the four corners than when it is located in the center. Simulation 1 shows that when the location of the communication receiver is not effectively determined, the number of distributed communication jamming systems is mostly between 16 and 20. However, if the main communication transmitter is in the center of the operational area, the required number increases sharply to 67. Simulation 2 shows that when the location of the communication receiver is fully determined (ΔR = 1000m), the number of distributed communication jamming systems is mostly between 10 and 15. However, if the main communication transmitter is in the center of the operational area, the required number increases to 32. Therefore, in conducting air assault operations, the selection of the air assault area should prioritize placing the main communication transmitter in one corner of the operational area.

[0085] (3) Fewer distributed communication jamming systems are needed when the location of the communication receiver is determined. Comparing the results of Simulation 1 and Simulation 2, when the location of the communication receiver is effectively determined, the number of distributed communication jamming systems required is 4-5 fewer than when the location is not determined. If the main communication transmitter is located in the center of the operational area, the number is reduced by 34. Therefore, the location of the communication receiver should be determined as much as possible before implementing distributed communication jamming.

[0086] Furthermore, embodiments of the present invention also provide a communication interference optimization configuration system based on two-level stochastic programming, including a computer device for executing the steps of the aforementioned communication interference optimization configuration method based on two-level stochastic programming.

[0087] This invention also provides a computer-readable storage medium storing a computer program to implement the aforementioned communication interference optimization configuration method based on two-layer stochastic programming.

[0088] Please note that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A communication interference optimization configuration method based on two-level stochastic programming, characterized in that, Includes the following steps: Step S1: Input the operational area's range (width, length), the maximum number N of distributed communication jamming systems, the required suppression duration T, and the effective suppression coefficient K. j Parameters of air defense wireless communication system and distributed communication jamming system, genetic generation number M, initial population size N ind Crossover probability p c and the mutation probability p m Raw calculation data; Step S2: Based on the original calculation data, generate the initial population for the distributed jamming system configuration location and the initial location (x) of the air defense wireless communication receiver. r0 ,y r0 ); Step S3: Based on the generated initial population and initial position (x) r0 ,y r0 The objective function value f(m) in the communication system optimization model is calculated using stochastic programming. The communication system optimization model is set as follows: In the formula, n m Here, N represents the number of distributed communication jamming systems in configuration scheme m, and N is the upper limit for the number of distributed communication jamming systems. Let m be the probability that configuration scheme m will effectively suppress wireless communication within time period T, 'a' be the confidence probability of achieving the minimum operational requirements, 'width' be the frontal width of the operational area, 'length' be the depth of the operational area, and 'x' be the location of the communication receiver. rm ,y rm Effective suppression probability P m J rt The power of the interference signal received by the communication receiver; S rt The signal power received by the communication receiver from the communication transmitter; Step S4: Calculate the fitness based on the objective function value, and perform selection, crossover, and mutation operations on the population to obtain a new generation of population; Step S5: Adjust the position of the air defense wireless communication receiver (x) rm ,y rm Then repeat steps S3 to S4 until m > M; Step S6: Calculate the minimum objective function value f during the solution process. min The population corresponding to (m) is taken as the optimal configuration scheme.

2. The method according to claim 1, characterized in that, The initial position (x) of the air defense wireless communication receiver in step S2 r0 ,y r0 Randomly select within the length and width range of the combat area.

3. The method according to claim 2, characterized in that, The effective suppression probability P in step S3 m The determination method is as follows: Let the position of the communication transmitter s be (x s ,y s The location of the communication receiver that initiates communication with it at time t is (x rt ,y rt If the m-th configuration scheme is used to implement distributed interference, the configuration locations of each distributed communication interference system are as follows: Where m i Let i be the configuration location of the i-th distributed communication jamming system. Then, the interference-to-signal ratio formed by the receiver at time t is: In the formula, J rt The power of the interference signal received by the communication receiver; S rt The signal power received by the communication receiver from the communication transmitter; P j G j P is the equivalent power of the jamming signal emitted by the distributed communication jamming system. t G t The equivalent power of the communication signal transmitted by the communication transmitter; γ j For the interference polarization loss of the distributed communication interference system; B rj R is the bandwidth ratio of the communication signal to the interference signal. rt q represents the distance between the receiver and transmitter in a communication system. rt Let be the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; q represents the antenna gain of the receiver in the direction of the transmitter; ri (θ) represents the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; Let q be the signal transmission loss of the i-th distributed communication interference system; rt Let be the antenna gain of the communication receiver in the direction of the i-th distributed communication jamming system; R represents the antenna gain of the receiver in the direction of the transmitter; rt R is the distance between the receiver and the transmitter. ri Let be the distance between the communication receiver and the i-th distributed communication jamming system; According to the analysis results of equation (1), in order for the wireless communication link to be effectively cut off at time t, the interference-to-signal ratio at the receiver end of the communication receiver must be greater than or equal to the effective suppression coefficient K. j ,Right now: The effective suppression probability P of implementing the configuration according to the m-th configuration scheme during time period T. m The calculation model is as follows: In the formula, rect(x) is the unit step function; T is the simulation duration.

4. The method according to claim 3, characterized in that: The location of the communication receiver (x) in step S3 rm ,y rm Set to: Location of the air defense system wireless communication receiver (x) rm ,y rm The calculation model is as follows: In the formula, (x r0 ,y r0 ) represents the initial position of the wireless communication receiver of the air defense system, which is usually randomly selected within the length and width range of the combat area; ΔR represents the positioning error; The angle of the current position relative to the center is rand(0,2π).

5. The method according to claim 3, characterized in that, Step S3 further includes: Step S31: Set the initial interference time t = 0, and the number of effective suppression attempts N. j =0; Step S32: Calculation Does it hold true? If it does, then N j =N j If t = t + 1 and t = t + 1, otherwise only execute t = t + 1; Step S33: Continue executing step S32 until t > T, then calculate... If the condition is met, then the number n of distributed communication interference systems can be calculated based on the current population. m This involves extracting the number of populations whose coordinates are not in (-1, -1) and calculating the objective function value accordingly. If the condition is not met, a penalty mechanism is activated, and the objective function value is determined to be f(m) = 1.

6. The method according to claim 5, characterized in that, The optimal configuration model for the distributed communication interference system in step S3 can be defined as follows:

7. The method according to claim 3, characterized in that, The conditions for determining the effective suppression probability are as follows: in the battlefield situation, all wireless communication links in the combat area use omnidirectional antennas and communicate within a unified frequency band, and the distributed communication jamming system can effectively target the working frequency band of wireless communication.

8. A communication interference optimization configuration system based on two-level stochastic programming, comprising computer equipment, characterized in that: The computer device is used to perform the steps of the communication interference optimization configuration method based on bi-level stochastic programming as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program to implement the communication interference optimization configuration method based on two-level stochastic programming as described in any one of claims 1 to 7.

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