Frequency spectrum confrontation resource and strategy optimization method based on multi-factor composite benefit

Abstract

The invention provides a spectrum adversarial resource and strategy optimization method based on multi-factor composite benefits. The method comprises the following steps: step 1, inputting multi-dimensional parameters; 2, calculating a multi-factor comprehensive confrontation benefit for a single target based on a multi-dimensional parameter; 3, taking the comprehensive confrontation benefit as an optimization target, and carrying out target distribution and strategy selection; and step 4, outputting a target allocation and strategy selection result. According to the method, multi-dimensional elements are comprehensively considered, a system comprehensive confrontation benefit analysis model is established, and confrontation benefits are comprehensively evaluated; when the resource allocation result is generated, adversarial strategy selection suggestions are provided, the diversity of algorithm output is improved, and application requirements are met.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic spectrum application, and in particular to a spectrum confrontation resource and strategy optimization method based on multi-factor composite benefits. Background Art

[0002] Resource allocation and strategy selection are the basis for electromagnetic spectrum confrontation decision-making. In particular, the rational allocation of resources in multi-target game scenarios is a necessary prerequisite and important means to achieve the overall confrontation effect and give full play to the capabilities of the spectrum confrontation system.

[0003] The traditional spectrum countermeasure resource allocation criteria are relatively simple, mainly considering factors such as the target threat situation, the probability of the target discovering the cover object, and the probability of suppressing the target. The factors such as frequency band, range, power, spatial angle, countermeasure strategy, etc. are not considered, and the factors considered are not comprehensive. In addition, the traditional algorithm does not comprehensively consider the combination of resource allocation and countermeasure strategy selection, but only generates resource allocation results for each target, lacking decision-making optimization of the strategy. Summary of the invention

[0004] In view of the problems that the traditional spectrum confrontation resource allocation algorithm has simple criteria, incomplete factors, and cannot generate strategy selection results, the present invention provides a spectrum confrontation resource and strategy optimization method based on multi-factor composite benefits, which comprehensively considers the combination of resource allocation and confrontation strategy selection, makes up for the defects of the traditional algorithm, and improves the utilization efficiency of spectrum confrontation resources.

[0005] The present invention provides a spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits, comprising the following steps:

[0006] Step 1, input multi-dimensional parameters;

[0007] Step 2: Calculate the multi-factor comprehensive confrontation benefits against a single target based on multi-dimensional parameters;

[0008] Step 3: Taking the comprehensive confrontation benefit as the optimization target, carry out target allocation and strategy selection;

[0009] Step 4: Output the target allocation and strategy selection results.

[0010] Further, step 1 comprises:

[0011] Input target parameters, including target number, location, minimum interference-to-signal ratio requirement γ, and maximum range maxR R 、Minimum operating frequency minrf R 、Maximum operating frequency maxrf R , threat level ω, purpose, average pulse width PW, transmission power P t 、Antenna main lobe gain G tand antenna sidelobe gain G s ;

[0012] Enter the countermeasure resource parameters, including the resource number, location, and minimum operating frequency minrf J 、Maximum operating frequency maxrf J 、Minimum azimuth minθ J 、Maximum azimuth angle maxθ J 、Minimum pitch angle minφ J 、Maximum pitch angle maxφ J , Transmitting power ERP J 、The number of targets that can be confronted at the same time maxNJR J and strategy set A;

[0013] Input the protected object parameters, including the protected object number, RCS (σ) and real-time position parameters;

[0014] Input fixed parameters, including the strategy evaluation parameter f(R i ,a) and the maximum benefit threshold maxf Ri ; R i represents the number of the i-th target; a is the strategy.

[0015] Furthermore, step 2 includes:

[0016] Calculate the signal-to-difference ratio f SNR (R i ,J j ,a),J j represents the number of the jth adversarial resource;

[0017] Calculate the frequency band efficiency f f (R i ,J j ,a);

[0018] Calculate power range efficiency f Dis (R i ,J j ,a);

[0019] Calculate the angle benefit f angle (R i ,J j ,a);

[0020] Calculate the strategy benefit f strategy (R i ,J j ,a);

[0021] Calculate the comprehensive benefits of multiple factors f(R i ,J j ,a);

[0022] Calculate the comprehensive confrontation benefit F of the system.

[0023] In a preferred solution, the signal-to-noise ratio is calculated SNR (R i ,J j ,a):

[0024] f SNR (Ri,Jj,a)=δ((J / S)ji-γi)

[0025] In the formula, R i Indicates the number of the i-th target; J j represents the number of the jth adversarial resource; (J / S)ji represents the interference-signal ratio of the jth resource against the i-th target; γi represents the minimum interference-signal ratio requirement of the i-th target; a is the strategy; δ(x) is the indicative function, defined as

[0026] In a preferred solution, the frequency band benefit f is calculated f (R i ,J j ,a):

[0027]

[0028] In the formula, Indicates resource J j The minimum operating frequency, Indicates resource J j The maximum operating frequency, Indicates the target R i The minimum operating frequency, Indicates the target R i The maximum operating frequency.

[0029] In a preferred solution, the power range benefit f is calculated Dis (R i ,J j ,a):

[0030]

[0031] In the formula, Dis(R i ,T) represents the target R i The distance to the object being protected; Indicates the maximum range of the target.

[0032] In a preferred solution, the angle benefit f is calculated angle (R i ,J j ,a):

[0033]

[0034] Where Δθ represents the azimuth of the cover object and the resource relative to the target, represents the pitch angle of the cover object and the resource relative to the target, k1 represents the azimuth influence factor, k2 represents the pitch influence factor; η is the base factor.

[0035] In a preferred solution, the strategy benefit f is calculated strategy (R i ,J j ,a):

[0036] f strategy (R i ,J j ,a)=f(R i ,a)

[0037] In the formula, f(R i ,a) is to use strategy a to target R i The evaluation function for implementing confrontation takes an integer value, and different strategies correspond to different integer values.

[0038] In a preferred solution, the multi-factor comprehensive benefit f(R i ,J i ,a) is the product of interference-to-signal ratio benefit, frequency band benefit, power range benefit, angle benefit and strategic benefit.

[0039] In a preferred solution, the comprehensive countermeasure benefit F of the calculation system is calculated.

[0040]

[0041] In the formula, ω i is the i-th target R i The threat level, maxf Ri is the maximum benefit threshold, a ij represents the strategy of resource j against target i, x ij Represents the state of resource j against target i.

[0042] Furthermore, in step 3, the comprehensive confrontation benefit is used as the optimization goal, constraints are set, and a heuristic search algorithm or a breadth-first or depth-first search algorithm is used to perform confrontation target allocation and strategy selection.

[0043] Furthermore, the constraints include:

[0044] Resources j The number of simultaneous attacks against multiple targets is no greater than maxNJR Jj ;maxNJR Jj Indicates the resource J in the input parameterj The number of targets that can be fought simultaneously;

[0045] Single target R i The number of resources that are simultaneously attacked is no more than maxNJ Ri ;maxNJ Ri Indicates the target R in the input parameter i The maximum number of resources to be confronted;

[0046] Single target R i The number of resources being countered at the same time is greater than or equal to 1.

[0047] Further, step 4 includes:

[0048] Output target allocation matrix X = {x ij}, x ij represents the state of resource j against target i;

[0049] Output strategy selection matrix A = {a ij}, a ij represents the strategy of resource j against target i, and its value is 0, a1,…, a k , where 0 means no confrontation and k means the number of strategies.

[0050] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0051] The present invention establishes a system comprehensive confrontation benefit analysis model by comprehensively considering multi-dimensional factors (interference-to-signal ratio, frequency band, power range, angle, strategy, etc.) to comprehensively evaluate the confrontation benefit; while generating resource allocation results, it provides confrontation strategy selection suggestions, thereby improving the diversity of algorithm output and meeting application requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The present invention is a flowchart of a spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0054] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Example

[0056] like Figure 1 As shown, this embodiment proposes a spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits, including the following steps:

[0057] Step 1: Input multi-dimensional parameters

[0058] 1) Input target parameters, including target number, location, minimum interference-to-signal ratio requirement γ, and maximum range maxR R 、Minimum operating frequency minrf R 、Maximum operating frequency maxrf R , threat level ω, purpose, average pulse width PW, transmission power P t 、Antenna main lobe gain G t , Antenna sidelobe gain G s ;

[0059] 2) Input the countermeasure resource parameters, including the resource number, location, and minimum operating frequency minrf J 、Maximum operating frequency maxrf J 、Minimum azimuth minθ J 、Maximum azimuth angle maxθ J 、Minimum pitch angle minφ J 、Maximum pitch angle maxφ J , Transmitting power ERP J 、The number of targets that can be confronted at the same time maxNJR J , strategy set A;

[0060] 3) Input the protected object parameters, including the protected object number, RCS (σ), and real-time position parameters;

[0061] 4) Input fixed parameters, including the strategy evaluation parameter f(R i ,a), Maximum benefit threshold maxf Ri .

[0062] Step 2: Calculate the multi-factor comprehensive confrontation benefits against a single target based on multi-dimensional parameters

[0063] 1) Calculate the signal-to-dry ratio benefit f SNR (R i ,J j ,a):

[0064] f SNR (Ri,Jj,a)=δ((J / S)ji-γi)

[0065] In the formula, R i Indicates the number of the i-th target; J j Indicates the number of the jth adversarial resource; (J / S) ji represents the interference signal ratio of the j-th resource against the i-th target; γ i represents the minimum interference-to-signal ratio requirement of the i-th target; a is the strategy; δ(x) is the indicative function, which is defined as follows:

[0066]

[0067] 2) Calculate the frequency band efficiency f f (R i ,J j ,a):

[0068]

[0069] In the formula, Indicates resource J j The minimum operating frequency, Indicates resource J j The maximum operating frequency, Indicates the target R i The minimum operating frequency, Indicates the target R i The maximum operating frequency.

[0070] 3) Calculate the power range benefit f Dis (R i ,J j ,a):

[0071]

[0072] In the formula, Dis(R i ,T) represents the target R i The distance to the object being protected; Indicates the maximum range of the target.

[0073] 4) Calculate the angle benefit f angle (R i ,J j ,a):

[0074]

[0075] Where Δθ represents the azimuth of the cover object and the resource relative to the target, represents the pitch angle of the cover object and the resource relative to the target, k1 represents the azimuth influence factor, k2 represents the pitch influence factor; η is the base factor. The calculation method of J / S can refer to relevant literature.

[0076] 5) Calculate the strategy benefit f strategy (R i ,J j ,a):

[0077] f strategy (R i ,J j ,a)=f(R i ,a)

[0078] In the formula, f(R i ,a) is to use strategy a to target R i The evaluation function for implementing confrontation takes an integer value in the range of [0,10]. Different strategies correspond to different integer values.

[0079] 6) Calculate the comprehensive benefits of multiple factors f(R i ,J j ,a)

[0080] f(R i ,J j ,a)=

[0081] f SNR (R i ,J j ,a)·f f (R i ,J j ,a)·f Dis (R i ,J j ,a)·f angle (R i ,J j ,a)·f strategy (R i ,J j ,a)

[0082] 7) Calculate the system's comprehensive countermeasures benefit F

[0083]

[0084] In the formula, ω i is the i-th target R i The threat level, maxf Ri is the maximum benefit threshold (the value range is (0,10000]), a ij represents the strategy of resource j against target i, x ijIndicates the state of resource j against target i (1 means confrontation, 0 means no confrontation).

[0085] Step 3: Taking comprehensive countermeasures as the optimization target, perform target allocation and strategy selection

[0086] Taking the comprehensive confrontation benefit as the optimization goal, setting the constraints as follows a), b), and c), using heuristic search algorithms, such as conventional genetic algorithms, branch-and-bound methods, or using breadth-first or depth-first search algorithms, confrontation target allocation and strategy selection can be performed.

[0087] a) Resource J j The number of simultaneous attacks against multiple targets is no greater than maxNJR Jj ;maxNJR Jj Indicates the resource J in the input parameter j The number of targets that can be fought simultaneously;

[0088] b) Single target R i The number of resources that are simultaneously attacked is no more than maxNJ Ri ;maxNJ Ri Indicates the target R in the input parameter i The maximum number of resources to be confronted;

[0089] c) Single target R i The number of resources being countered at the same time is greater than or equal to 1.

[0090] Step 4: Output target allocation and strategy selection results

[0091] Output target allocation matrix X = {x ij}, x ij Indicates the state of resource j against target i (1 for confrontation, 0 for non-confrontation);

[0092] Output strategy selection matrix A = {a ij}, a ij represents the strategy of resource j against target i, and its value is 0, a1,…, a k , where 0 means no confrontation and k means the number of strategies.

[0093] Example:

[0094] Step 1: Input multi-dimensional parameters

[0095] 1) Input the target parameters as shown in Table 1.

[0096] Table 1, target parameters:

[0097]

[0098] 2) Input the adversarial resource parameters, as shown in Table 2 and Table 3.

[0099] Table 2, counter resource parameters:

[0100]

[0101] Table 3, strategy set:

[0102] Strategy Number Policy Content <![CDATA[a1]]> Strategy 1 <![CDATA[a2]]> Strategy 2 <![CDATA[a3]]> Strategy 3 <![CDATA[a4]]> Strategy 4

[0103] 3) Input the parameters of the protected object, as shown in Table 4.

[0104] Table 4, parameters of the protected object:

[0105] serial number RCS Location (northeast celestial coordinates) 501 <![CDATA[1m 2 ]]> (240,0,1)km

[0106] 4) Input fixed parameters as shown in Table 5.

[0107]

[0108] Set the maximum confrontation benefit threshold maxf Ri According to the target purpose, the maximum benefit thresholds for warning, aiming and fire control purposes are set to 1000, 2000 and 5000 respectively.

[0109] Step 2: Calculate the multi-factor comprehensive confrontation benefits against a single target based on multi-dimensional parameters

[0110] The comprehensive counter-effectiveness of each resource to each target corresponding to the selection strategies a1~a4 is shown in Table 6, Table 7, Table 8, and Table 9.

[0111] Table 6, comprehensive confrontation benefits corresponding to strategy a1:

[0112] Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 626.12 162.00 155.02 239.34 Resources 102 653.57 175.82 168.85 255.84 Resources 201 633.33 164.44 160.95 243.48 Resources 202 660.78 178.26 174.78 258.36

[0113] Table 7, comprehensive confrontation benefits corresponding to strategy a2:

[0114] Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 313.06 32.40 31.00 47.87 Resources 102 326.79 35.16 33.77 51.16 Resources 201 316.67 32.89 32.19 48.70 Resources 202 330.39 35.65 34.96 51.67

[0115] Table 8, comprehensive countermeasure benefits corresponding to strategy a3:

[0116] Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 438.29 324.01 217.02 239.34 Resources 102 457.50 351.64 236.39 255.81 Resources 201 443.33 328.89 225.33 243.48 Resources 202 462.55 356.53 244.70 258.36

[0117] Table 9, comprehensive confrontation benefits corresponding to strategy a4:

[0118] Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 125.22 64.80 310.03 478.69 Resources 102 130.71 70.33 337.69 511.63 Resources 201 126.67 65.78 321.91 486.97 Resources 202 132.16 71.31 349.57 516.72

[0119] Step 3: Taking comprehensive countermeasures as the optimization target, perform target allocation and strategy selection

[0120] Taking the comprehensive confrontation benefit as the fitness function, the constraints are set as follows, and the conventional genetic algorithm or search algorithm is used to perform target allocation and strategy selection.

[0121] a) Resource J j The number of targets to be attacked simultaneously shall not exceed 2;

[0122] b) Single target R i The number of resources being confronted at the same time is no more than 3;

[0123] c) Single target R i The number of resources being countered at the same time is greater than or equal to 1.

[0124] Step 4: Output target allocation and strategy selection results

[0125] Output the adversarial target allocation matrix of each resource:

[0126]

[0127] Table 10, target allocation results:

[0128] Whether to fight Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 confrontation confrontation No confrontation No confrontation Resources 102 No confrontation No confrontation confrontation confrontation Resources 201 No confrontation confrontation No confrontation confrontation Resources 202 No confrontation confrontation confrontation No confrontation

[0129] Output the strategy selection matrix for each resource:

[0130]

[0131] Its physical meaning is shown in Table 11:

[0132] Strategy Target 6001 Target 1001 Target 1002 Target 4001 Resources 101 <![CDATA[a1]]> <![CDATA[a3]]> -(No confrontation) -(No confrontation) Resources 102 -(No confrontation) -(No confrontation) <![CDATA[a4]]> <![CDATA[a4]]> Resources 201 -(No confrontation) <![CDATA[a3]]> -(No confrontation) <![CDATA[a4]]> Resources 202 -(No confrontation) <![CDATA[a3]]> <![CDATA[a4]]> -(No confrontation)

[0133] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits, characterized in that: The steps include: Step 1, input multi-dimensional parameters; Step 2: Calculate the multi-factor comprehensive confrontation benefits against a single target based on multi-dimensional parameters; Step 3: Taking the comprehensive confrontation benefit as the optimization target, carry out target allocation and strategy selection; Step 4: Output the target allocation and strategy selection results.

2. The spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits according to claim 1 is characterized in that: Step 1 includes: Input target parameters, including target number, location, minimum interference-to-signal ratio requirement γ, and maximum range maxR R 、Minimum operating frequency minrf R 、Maximum operating frequency maxrf R 、Maximum number of resources to be confronted maxNJ R , threat level ω, purpose, average pulse width PW, transmission power P t 、Antenna main lobe gain G t and antenna sidelobe gain G s ; Enter the countermeasure resource parameters, including the resource number, location, and minimum operating frequency minrf J 、Maximum operating frequency maxrf J 、Minimum azimuth minθ J 、Maximum azimuth angle maxθ J 、Minimum pitch angle minφ J 、Maximum pitch angle maxφ J , Transmitting power ERP J 、The number of targets that can be confronted at the same time maxNJR J and strategy set A; Input the parameters of the protected object, including the number, RCS (σ) and real-time position parameters of the protected object; Input fixed parameters, including the strategy evaluation parameter f(R i ,a) and the maximum benefit threshold maxf Ri ; R i represents the number of the i-th target; a is the strategy.

3. The spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits according to claim 2 is characterized in that: Step 2 includes: Calculate the signal-to-difference ratio f SNR (R i ,J j ,a),J j represents the number of the jth adversarial resource; Calculate the frequency band efficiency f f (R i ,J j ,a); Calculate power range efficiency f Dis (R i ,J j ,a); Calculate the angle benefit f angle (R i ,J j ,a); Calculate the strategy benefit f strategy (R i ,J j ,a); Calculate the comprehensive benefits of multiple factors f(R i ,J j ,a); Calculate the comprehensive confrontation benefit F of the system.

4. The spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits according to claim 3 is characterized in that: Calculate the signal-to-difference ratio f SNR (R i ,J j ,a): f SNR (Ri,Jj,a)=δ((J / S)ji-γi) In the formula, R i Indicates the number of the i-th target; J j represents the number of the jth adversarial resource; (J / S)ji represents the interference-signal ratio of the jth resource against the i-th target; γi represents the minimum interference-signal ratio requirement of the i-th target; a is the strategy; δ(x) is the indicative function, defined as 5. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Calculate the frequency band efficiency f f (R i ,J j ,a): In the formula, Indicates resource J j The minimum operating frequency, Indicates resource J j The maximum operating frequency, Indicates the target R i The minimum operating frequency, Indicates the target R i The maximum operating frequency.

6. The spectrum countermeasure resource and strategy optimization method based on multi-factor composite benefits according to claim 3 is characterized in that: Calculate power range efficiency f Dis (R i ,J j ,a): In the formula, Dis(R i ,T) represents the target R i The distance to the object being protected; Indicates the maximum range of the target.

7. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Calculate the angle benefit f angle (R i ,J j ,a): Where Δθ represents the azimuth of the cover object and the resource relative to the target, represents the pitch angle of the cover object and the resource relative to the target, k1 represents the azimuth influence factor, k2 represents the pitch influence factor; η is the base factor.

8. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Calculate the strategy benefit f strategy (R i ,J j ,a): f strategy (R i ,J j ,a)=f(R i ,a) In the formula, f(R i ,a) is to use strategy a to target R i The evaluation function for implementing confrontation takes an integer value, and different strategies correspond to different integer values.

9. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Calculate the comprehensive benefits of multiple factors f(R i ,J i ,a ij ) is the product of the interference-to-signal ratio benefit, frequency band benefit, power range benefit, angle benefit and strategic benefit.

10. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Calculate the comprehensive countermeasure benefit of the system F In the formula, ω i is the i-th target R i The threat level, maxf Ri For the target R i The maximum benefit threshold, a ij represents the strategy of resource j against target i, x ij Represents the state of resource j against target i.

11. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 2 is characterized in that: In step 3, the comprehensive confrontation benefit is taken as the optimization goal, constraints are set, and heuristic search algorithms or breadth-first or depth-first search algorithms are used to allocate confrontation targets and select strategies.

12. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 11, characterized in that: The constraints include: Resources j The number of simultaneous attacks against multiple targets is no greater than maxNJR Jj ;maxNJR Jj Indicates the resource J in the input parameter j The number of targets that can be fought simultaneously; Single target R i The number of resources that are simultaneously attacked is no more than maxNJ Ri ;maxNJ Ri Indicates the target R in the input parameter i The maximum number of resources to be confronted; Single target R i The number of resources being countered at the same time is greater than or equal to 1.

13. The spectrum countermeasure resource and strategy optimization method based on multi-factor compound benefits according to claim 3 is characterized in that: Step 4 includes: Output target allocation matrix X = {x ij }, x ij represents the state of resource j against target i; Output strategy selection matrix A = {a ij }, a ij represents the strategy of resource j against target i, and its value is 0, a1,…, a k , where 0 means no confrontation and k means the number of strategies.

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