A method and system for similarity analysis of electronic blue force simulation devices

Abstract

The application discloses an electronic blue army simulation equipment similarity analysis method and system, and the method comprises the steps of determining an electronic blue army simulation similarity evaluation object, determining an electronic blue army simulation similarity evaluation index system based on the electronic blue army simulation similarity evaluation object, performing electronic blue army simulation single-dimension similarity analysis calculation based on the electronic blue army simulation similarity evaluation index system, obtaining a similarity score of a target dimension index system set, performing electronic blue army simulation multi-dimension similarity analysis calculation based on the similarity scores of all dimension index system sets, determining the similarity of the electronic blue army simulation equipment, and judging the accuracy of the blue army simulation equipment simulation according to the determined similarity of the electronic blue army simulation equipment.

Description

Technical Field

[0001] This invention relates to a method and system for similarity analysis of electronic blue force simulation equipment, belonging to the field of military equipment confrontation simulation training. Background Technology

[0002] In weapons and equipment testing and training, simulating enemy weapons and equipment and organizing tactical deployments to engage in combat against our own equipment is a crucial method for testing the combat readiness of our military equipment. To realistically recreate the enemy's combat capabilities and construct realistic red-blue force-versus-force training scenarios, it is necessary to build realistic blue force simulation equipment to test the combat capabilities of the red force's military equipment in a near-realistic environment. To effectively evaluate the realistic performance capability of the blue force simulation equipment, it is necessary to construct an effective evaluation index system and evaluation methods from multiple dimensions to objectively assess the degree of similarity between the blue force simulation equipment and the real enemy equipment.

[0003] In existing technologies, constructing opposing force simulation equipment using the exact same method is costly and impossible due to technological blockades. Considering principles of realism, adversarial nature, and economy, opposing force simulation equipment is generally constructed using equivalent simulation methods, building a simulated opposing force through digital simulation and real-world equipment simulation. For example, patents such as "Chinese Patent CN201811009780.0: A Similarity Calculation Method Based on Real-World Equipment Combat Technical Indicators," "Research on Similarity Matching Problem of Air Force Equipment Mapping Simulated Opposing Force," and "Similarity Evaluation of Opposing Force Air Formation Based on Improved Analytic Hierarchy Process" propose similarity calculation methods based on real-world equipment indicator characteristics. These methods perform horizontal comparisons of equipment technical and tactical performance indicators, providing similarity evaluation results for each indicator. However, they lack evaluation of system capabilities, tactics, and adversarial effects, and have not yet formed a comprehensive similarity evaluation result to determine the accuracy of the constructed opposing force simulation equipment. Summary of the Invention

[0004] Objective: To overcome the shortcomings of existing technologies, this invention provides a method and system for similarity analysis of electronic blue team simulation equipment, enabling similarity analysis and calculation of electronic blue team simulation equipment against equivalent opponents; it can evaluate the similarity of electronic blue team simulation in a certain dimension, or perform a comprehensive evaluation of the similarity of electronic blue team simulation.

[0005] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, the present invention provides a method for similarity analysis of electronic blue team simulation equipment, comprising:

[0007] Identify the objects to be evaluated in the electronic blue team simulation similarity assessment;

[0008] Based on the aforementioned electronic blue team simulation similarity evaluation objects, an electronic blue team simulation similarity evaluation index system is determined;

[0009] Based on the electronic blue team simulation similarity evaluation index system, a single-dimensional similarity analysis and calculation of the electronic blue team simulation is carried out to obtain the similarity score of the target dimension index system set.

[0010] Based on the similarity scores of all dimensions of the indicator system, a multi-dimensional similarity analysis of the electronic blue team simulation is performed to determine the similarity of the electronic blue team simulation equipment.

[0011] Based on the determined similarity of the electronic blue team simulation equipment, the accuracy of the blue team simulation equipment is judged.

[0012] In some embodiments, determining the electronic blue team simulation similarity evaluation object includes:

[0013] Identify the electronic blue team simulation device A1 and its simulation object A2, forming the evaluation object set A = {A1, A2}.

[0014] In some embodiments, an electronic blue team simulation similarity evaluation index system is determined, including:

[0015] An evaluation index system set B = {B1, B2, ..., B6} is established from multiple dimensions, including the technical system index set B1, functional index set B2, technical performance index set B3, system capability index set B4, tactical application index set B5, and confrontation effect index set B6 of electronic blue force simulation equipment. k}, where k is the total number of indicators in the evaluation indicator system set.

[0016] In some embodiments, the electronic blue team simulation single-dimensional similarity analysis calculation includes:

[0017] Let B be the target dimension index system set for electronic blue team simulation equipment. n Given m indicators c1, c2, ..., c m composition;

[0018] Based on the theory of similar systems, individual indices c1, c2, ..., c are determined. m The similarity score D = {d1, d2, ..., d...} m};

[0019] Using the analytic hierarchy process (AHP) or a modified AHP, calculate the individual indices c1, c2, ..., c m The weighting coefficients W = {w1, w2, ..., w m} T ;

[0020] Calculate the indicator system set B n Similarity score b n=D·W.

[0021] In some embodiments, individual indices c1, c2, ..., c are determined based on similarity system theory. m The similarity score D = {d1, d2, ..., d...} m},include:

[0022] Based on similarity system theory, and according to the type and characteristics of the indicators, a similarity factor d for a single indicator is established in the form of "precise value-precise value", "precise value-interval value", "interval value-interval value", or "enumerated value-enumerated value". i Model.

[0023] Furthermore, using the analytic hierarchy process (AHP) or a modified AHP, individual indices c1, c2, ..., c are calculated. m The weighting coefficients W = {w1, w2, ..., w m} T ,include:

[0024] Determine the relative importance of each pair of indicators. ij This forms the judgment matrix C = {c ij ,i=1,2,…,m; j=1,2,…,m};

[0025] Find the largest eigenvalue and eigenvector of the judgment matrix C;

[0026] CW=λ max W

[0027] Where, λ max To determine the largest eigenvalue of matrix C, let W = [w1, w2, ..., w...]. m ] T To determine the eigenvectors of moment C, i.e., indices c1, c2, ..., c... m The corresponding weighting coefficients.

[0028] Furthermore, it also includes a consistency check on the judgment matrix C:

[0029] CR c =CI c / RI c

[0030] Among them, CI c As a consistency indicator, RI c CR is the average random consistency index. c To calculate the random consistency ratio;

[0031] When CR c If the value is ≤0.1, the judgment matrix C is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

[0032] RI c CI was obtained by looking up a table. c The calculation formula is as follows:

[0033] CI c =(λ max -m) / (m-1)

[0034] Where m is the order of the judgment matrix C.

[0035] In some embodiments, the electronic blue team simulates multi-dimensional similarity analysis calculations, including:

[0036] Based on the evaluation index system set B = {B1, B2, ..., B...} k The similarity score b for each dimension of the indicator system set in} i This forms a score set E = {e} for each dimension. i , i = 1, 2, ..., k}; where e i =b i / ∑b j ,i=1,2,…,k; j=1,2,…,k;

[0037] Using the analytic hierarchy process (AHP) or its modified form, calculate the indicator set B1, B2, ..., B for each dimension. k The weighting coefficients V = {v1, v2, ..., v k} T ;

[0038] Calculate the multi-dimensional similarity score b = E·V for the electronic blue team simulation equipment.

[0039] Furthermore, using the analytic hierarchy process (AHP) or a modified AHP, the indicator sets B1, B2, ..., B for each dimension are calculated. k The weighting coefficients V = {v1, v2, ..., v k} T ,include:

[0040] Determine the relative importance of the judgment relationship between two sets of indicator dimensions a ij This forms the judgment matrix A = {a} ij ,i=1,2,…,k;j=1,2,…,k};

[0041] Find the largest eigenvalue and eigenvector of the judgment matrix A;

[0042] AV = ρ max V

[0043] Where, ρ max To determine the largest eigenvalue of matrix A, V = [v1, v2, ..., v...]. k] T To determine the eigenvectors of moment A, i.e., the index set B1, B2, ..., B k The corresponding weighting coefficients.

[0044] Furthermore, it also includes a consistency check on the judgment matrix A:

[0045] CR A =CI A / RI A

[0046] Among them, CI A As a consistency indicator, RI A CR is the average random consistency index. A To calculate the random consistency ratio;

[0047] When CR A If the value is ≤0.1, the judgment matrix A is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

[0048] In some embodiments, RI A CI was obtained by looking up a table. A The calculation formula is as follows:

[0049] CI A =(ρ max –k) / (k-1)

[0050] Where, ρ max Let k be the largest eigenvalue of matrix A, and k be the order of matrix C.

[0051] This invention addresses the problem of objectively evaluating the realism of electronic opposing force simulation equipment during its demonstration, development, and testing. On one hand, it quantitatively analyzes the similarity of the simulated opposing force environment, assesses the simulated adversarial environment, and supports the evaluation of weapon and equipment test results and training effectiveness. On the other hand, it provides scientifically sound suggestions for potential technical approaches to improve the realism of the simulation equipment.

[0052] Secondly, the present invention provides an electronic blue team simulation device similarity analysis system, comprising:

[0053] The evaluation object determination module is used to: determine the objects for electronic blue team simulation similarity evaluation;

[0054] The evaluation index system determination module is used to: determine the electronic blue team simulation similarity evaluation index system based on the electronic blue team simulation similarity evaluation object;

[0055] The single-dimensional similarity calculation module is used to: perform single-dimensional similarity analysis and calculation of electronic blue team simulation based on the electronic blue team simulation similarity evaluation index system, and obtain the similarity score of the target dimension index system set;

[0056] The multi-dimensional similarity calculation module is used to: perform multi-dimensional similarity analysis and calculation for electronic blue team simulation based on the similarity score of all dimension indicator system sets, and determine the similarity of electronic blue team simulation equipment;

[0057] The judgment module is used to determine the accuracy of the simulation by the blue team simulation equipment based on the determined similarity of the electronic blue team simulation equipment.

[0058] In this application, the consistency test of the judgment matrix is ​​performed. If the consistency test is passed, it means that the analysis and calculation results are reliable. Otherwise, the judgment matrix is ​​modified and recalculated until the consistency test requirements are met.

[0059] Thirdly, the present invention provides an apparatus comprising,

[0060] Memory;

[0061] processor;

[0062] as well as

[0063] Computer programs;

[0064] The computer program is stored in the memory and configured to be executed by the processor to implement the method described in the first aspect above.

[0065] Fourthly, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0066] Beneficial Effects: The electronic blue force simulation equipment similarity analysis method and system provided by this invention have the following advantages: This invention proposes a scientific, objective, reasonable, and feasible method for calculating the similarity of electronic blue force simulation equipment. It comprehensively evaluates the accuracy of electronic blue force simulation equipment simulation from multiple dimensions, including technical system indicators, functional indicators, technical performance indicators, system capability indicators, tactical application indicators, and confrontation effects. This provides important theoretical and data support for the construction of electronic blue force confrontation environments during weapon equipment testing and training. It solves the problem of objectively judging the "similarity" of simulations during the demonstration, development, and testing and training of electronic blue force simulation equipment. On the one hand, it quantitatively analyzes the similarity of blue force simulations and evaluates the simulated blue force confrontation environment, supporting the evaluation of weapon equipment test results and training effectiveness. On the other hand, it provides scientific and reasonable suggestions for possible technical approaches to improve the realism of blue force simulation equipment simulations. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of an electronic blue team simulation device similarity analysis method according to an embodiment of the present invention;

[0068] Figure 2 This is a schematic diagram of an electronic blue team simulation device similarity analysis system according to an embodiment of the present invention. Detailed Implementation

[0069] The present invention will be further described below with reference to the accompanying drawings and embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and should not be used to limit the scope of protection of the present invention.

[0070] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0071] In the description of this invention, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0072] Example 1

[0073] Firstly, such as Figure 1 As shown, this embodiment provides a method for similarity analysis of electronic blue team simulation equipment, including:

[0074] Identify the objects to be evaluated in the electronic blue team simulation similarity assessment;

[0075] Based on the aforementioned electronic blue team simulation similarity evaluation objects, an electronic blue team simulation similarity evaluation index system is determined;

[0076] Based on the electronic blue team simulation similarity evaluation index system, a single-dimensional similarity analysis and calculation of the electronic blue team simulation is carried out to obtain the similarity score of the target dimension index system set.

[0077] Based on the similarity scores of all dimensions of the indicator system, a multi-dimensional similarity analysis of the electronic blue team simulation is performed to determine the similarity of the electronic blue team simulation equipment.

[0078] Based on the determined similarity of the electronic blue team simulation equipment.

[0079] In some embodiments, determining the electronic blue team simulation similarity evaluation object includes:

[0080] Identify the electronic blue team simulation device A1 and its simulation object A2, forming the evaluation object set A = {A1, A2}.

[0081] In some embodiments, an electronic blue team simulation similarity evaluation index system is determined, including:

[0082] An evaluation index system set B = {B1, B2, ..., B6} is established from multiple dimensions, including the technical system index set B1, functional index set B2, technical performance index set B3, system capability index set B4, tactical application index set B5, and confrontation effect index set B6 of electronic blue force simulation equipment. k}, where k is the total number of indicators in the evaluation indicator system set.

[0083] In some embodiments, the electronic blue team simulation single-dimensional similarity analysis calculation includes:

[0084] Let B be the target dimension index system set for electronic blue team simulation equipment. n Given m indicators c1, c2, ..., c m Composition; for example, in this embodiment, when the electronic blue force simulation equipment is a shipborne active jamming simulation equipment, the technical performance index system set B3 consists of 7 indicators: working frequency band c1, equivalent radiated power c2, working mode c3, airspace coverage c4, jamming pattern c5, detection mode c6, and transmission and reception mode c7.

[0085] Based on the theory of similar systems, the similarity score D = {d1, d2, ..., d7} for individual indicators c1, c2, ..., c7 is determined.

[0086] Using the analytic hierarchy process (AHP) or a modified AHP, calculate the weight coefficients W = {w1, w2, ..., w7} for each individual indicator c1, c2, ..., c7. T ;

[0087] Calculate the similarity score b3 = D·W for the indicator system set B3.

[0088] In some embodiments, based on similarity system theory, the similarity score D = {d1, d2, ..., d7} for individual indicators c1, c2, ..., c7 is determined, including:

[0089] Based on similarity system theory, and according to the type and characteristics of the indicators, a similarity factor d for a single indicator is established in the form of "precise value-precise value", "precise value-interval value", "interval value-interval value", or "enumerated value-enumerated value".i Model.

[0090] Furthermore, using the analytic hierarchy process (AHP) or a modified AHP, the weight coefficients W = {w1, w2, ..., w7} of each individual indicator c1, c2, ..., c7 are calculated. T ,include:

[0091] Determine the relative importance of each pair of indicators. ij This forms the judgment matrix C = {c ij ,i=1,2,…,7; j=1,2,…,7};

[0092] Find the largest eigenvalue and eigenvector of the judgment matrix C;

[0093] CW=λ max W

[0094] Where, λ max To determine the largest eigenvalue of matrix C, let W = [w1, w2, ..., w7]. T The eigenvectors of the judgment moment C are the weight coefficients corresponding to the indices c1, c2, ..., c7.

[0095] Furthermore, it also includes a consistency check on the judgment matrix C:

[0096] CR c =CI c / RI c

[0097] Among them, CI c As a consistency indicator, RI c CR is the average random consistency index. c To calculate the random consistency ratio;

[0098] When CR c If the value is ≤0.1, the judgment matrix C is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

[0099] Furthermore, in some embodiments, RI c CI was obtained by looking up a table. c The calculation formula is as follows:

[0100] CI c =(λ max -m) / (m-1)

[0101] Where m is the order of the judgment matrix C.

[0102] In some embodiments, the electronic blue team simulates multi-dimensional similarity analysis calculations, including:

[0103] Based on the evaluation index system set B = {B1, B2, ..., B...} k The similarity score b for each dimension of the indicator system set in} i This forms a score set E = {e} for each dimension. i , i = 1, 2, ..., k}; where e i =b i / ∑b j ,i=1,2,…,k; j=1,2,…,k;

[0104] Using the analytic hierarchy process (AHP) or its modified form, calculate the indicator set B1, B2, ..., B for each dimension. k The weighting coefficients V = {v1, v2, ..., v k} T ;

[0105] Calculate the multi-dimensional similarity score b = E·V for the electronic blue team simulation equipment.

[0106] Furthermore, using the analytic hierarchy process (AHP) or a modified AHP, the indicator sets B1, B2, ..., B for each dimension are calculated. k The weighting coefficients V = {v1, v2, ..., v k} T ,include:

[0107] Determine the relative importance of the judgment relationship between two sets of indicator dimensions a ij This forms the judgment matrix A = {a} ij ,i=1,2,…,k;j=1,2,…,k};

[0108] Find the largest eigenvalue and eigenvector of the judgment matrix A;

[0109] AV = ρ max V

[0110] Where, ρ max To determine the largest eigenvalue of matrix A, V = [v1, v2, ..., v...]. k ] T To determine the eigenvectors of moment A, i.e., the index set B1, B2, ..., B k The corresponding weighting coefficients.

[0111] Furthermore, it also includes a consistency check on the judgment matrix A:

[0112] CR A =CI A / RI A

[0113] Among them, CI A As a consistency indicator, RIA CR is the average random consistency index. A To calculate the random consistency ratio;

[0114] When CR A If the value is ≤0.1, the judgment matrix A is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

[0115] Furthermore, in some embodiments, RI A CI was obtained by looking up a table. A The calculation formula is as follows:

[0116] CI A =(ρ max –k) / (k-1)

[0117] Where, ρ max Let k be the largest eigenvalue of matrix A, and k be the order of matrix C.

[0118] In summary, this invention determines an electronic blue force simulation similarity evaluation index system based on the object of the electronic blue force simulation similarity evaluation; based on the electronic blue force simulation similarity evaluation index system, it performs single-dimensional similarity analysis and calculation to obtain the similarity score of the target dimension index system set; based on the similarity scores of all dimension index system sets, it performs multi-dimensional similarity analysis and calculation to determine the similarity of the electronic blue force simulation equipment; and based on the determined similarity of the electronic blue force simulation equipment, it judges the accuracy of the blue force simulation equipment simulation, thus solving the problem of objectively judging whether the simulation is "similar" during the demonstration, development, and testing training of electronic blue force simulation equipment. On the one hand, it quantitatively analyzes the similarity of the blue force simulation and evaluates the simulated blue force confrontation environment, supporting the evaluation of weapon and equipment test results and training effectiveness; on the other hand, it provides scientific and reasonable suggestions for possible technical approaches to improve the realism of the blue force simulation equipment simulation.

[0119] Example 2

[0120] Secondly, based on Embodiment 1, this embodiment provides an electronic blue team simulation equipment similarity analysis system, including a processor and a storage medium;

[0121] The storage medium is used to store instructions;

[0122] The processor is configured to operate according to the instructions to execute the method according to Embodiment 1.

[0123] In some embodiments, such as Figure 2 As shown, the electronic blue team simulation equipment similarity analysis system includes:

[0124] The evaluation object determination module is used to: determine the objects for electronic blue team simulation similarity evaluation;

[0125] The evaluation index system determination module is used to: determine the electronic blue team simulation similarity evaluation index system based on the electronic blue team simulation similarity evaluation object;

[0126] The single-dimensional similarity calculation module is used to: perform single-dimensional similarity analysis and calculation of electronic blue team simulation based on the electronic blue team simulation similarity evaluation index system, and obtain the similarity score of the target dimension index system set;

[0127] The multi-dimensional similarity calculation module is used to: perform multi-dimensional similarity analysis and calculation for electronic blue team simulation based on the similarity score of all dimension indicator system sets, and determine the similarity of electronic blue team simulation equipment;

[0128] The judgment module is used to determine the accuracy of the simulation by the blue team simulation equipment based on the determined similarity of the electronic blue team simulation equipment.

[0129] This embodiment uses a consistency check of the judgment matrix. If the consistency check is passed, the analysis and calculation results are considered reliable. Otherwise, the judgment matrix is ​​corrected and recalculated until the consistency check requirements are met.

[0130] Example 3

[0131] Thirdly, based on Embodiment 1, this embodiment provides a device, including,

[0132] Memory;

[0133] processor;

[0134] as well as

[0135] Computer programs;

[0136] The computer program is stored in the memory and configured to be executed by the processor to implement the method described in Embodiment 1.

[0137] Example 4

[0138] Fourthly, based on Embodiment 1, this embodiment provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, it implements the method described in Embodiment 1.

[0139] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0140] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0141] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0143] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for similarity analysis of electronic blue team simulation equipment, characterized in that, The method includes: Identify the objects to be evaluated in the electronic blue team simulation similarity assessment; Based on the aforementioned electronic blue team simulation similarity evaluation objects, an electronic blue team simulation similarity evaluation index system is determined; Based on the electronic blue team simulation similarity evaluation index system, a single-dimensional similarity analysis and calculation of the electronic blue team simulation is carried out to obtain the similarity score of the target dimension index system set. Based on the similarity scores of all dimensions of the indicator system, a multi-dimensional similarity analysis of the electronic blue team simulation is performed to determine the similarity of the electronic blue team simulation equipment. Based on the determined similarity of the electronic blue team simulation equipment, the accuracy of the blue team simulation equipment is judged.

2. The electronic blue team simulation equipment similarity analysis method according to claim 1, characterized in that, Identify the objects for electronic blue team simulation similarity evaluation, including: Identify the electronic blue team simulation device A1 and its simulation object A2, forming the evaluation object set A = {A1, A2}; And / or, determine the electronic blue team simulation similarity evaluation index system, including: An evaluation index system set B = {B1, B2, ..., B6} is established from multiple dimensions, including the technical system index set B1, functional index set B2, technical performance index set B3, system capability index set B4, tactical application index set B5, and confrontation effect index set B6 of electronic blue force simulation equipment. k }, where k is the total number of indicators in the evaluation indicator system set.

3. The electronic blue team simulation equipment similarity analysis method according to claim 1, characterized in that, The electronic blue team simulation single-dimensional similarity analysis calculation includes: Let B be the target dimension index system set for electronic blue team simulation equipment. n Given m indicators c1, c2, ..., c m composition; Based on the theory of similar systems, individual indices c1, c2, ..., c are determined. m The similarity score D = {d1, d2, ..., d...} m }; Using the analytic hierarchy process (AHP) or a modified AHP, calculate the individual indices c1, c2, ..., c m The weighting coefficients W = {w1, w2, ..., w m } T ; Calculate the indicator system set B n Similarity score b n =D·W.

4. The electronic blue team simulation equipment similarity analysis method according to claim 3, characterized in that, Based on the theory of similar systems, individual indices c1, c2, ..., c are determined. m The similarity score D = {d1, d2, ..., d...} m },include: Based on the theory of similar systems, and according to the type and characteristics of the indicators, a similarity factor d for a single indicator is established in the form of "exact value-exact value", "exact value-interval value", "interval value-interval value", or "enumerated value-enumerated value". i Model.

5. The electronic blue team simulation equipment similarity analysis method according to claim 3, characterized in that, Using the analytic hierarchy process (AHP) or a modified AHP, calculate the individual indices c1, c2, ..., c m The weighting coefficients W = {w1, w2, ..., w m } T ,include: Determine the relative importance of each pair of indicators. ij This forms the judgment matrix C = {c ij ,i=1,2,…,m; j=1,2,…,m}; Find the largest eigenvalue and eigenvector of the judgment matrix C; CW=λ max IN Where, λ max To determine the largest eigenvalue of matrix C, let W = [w1, w2, ..., w...]. m ] T To determine the eigenvectors of moment C, i.e., indices c1, c2, ..., c... m The corresponding weighting coefficients.

6. The electronic blue team simulation equipment similarity analysis method according to claim 5, characterized in that, This also includes a consistency check on the judgment matrix C: CR c =CI c / RI c Among them, CI c As a consistency indicator, RI c CR is the average random consistency index. c To calculate the random consistency ratio; When CR c If the value is ≤0.1, the judgment matrix C is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

7. The electronic blue team simulation equipment similarity analysis method according to claim 1, characterized in that, Electronic Blue Team Simulation Multi-Dimensional Similarity Analysis Calculation, including: Based on the evaluation index system set B = {B1, B2, ..., B...} k The similarity score b for each dimension of the indicator system set in} i This forms a score set E = {e} for each dimension. i , i = 1, 2, ..., k}; where e i =b i / ∑b j ,i=1,2,…,k; j=1,2,…,k; Using the analytic hierarchy process (AHP) or its modified form, calculate the indicator set B1, B2, ..., B for each dimension. k The weighting coefficients V = {v1, v2, ..., v k } T ; Calculate the multi-dimensional similarity score b = E·V for the electronic blue team simulation equipment.

8. The electronic blue team simulation equipment similarity analysis method according to claim 7, characterized in that, Using the analytic hierarchy process (AHP) or its modified form, calculate the indicator set B1, B2, ..., B for each dimension. k The weighting coefficients V = {v1, v2, ..., v k } T ,include: Determine the relative importance of the judgment relationship between two sets of indicator dimensions a ij This forms the judgment matrix A = {a} ij ,i=1,2,…,k;j=1,2,…,k}; Find the largest eigenvalue and eigenvector of the judgment matrix A; OFF=ρ max V Where, ρ max To determine the largest eigenvalue of matrix A, V = [v1, v2, ..., v...]. k ] T To determine the eigenvectors of moment A, i.e., the index set B1, B2, ..., B k The corresponding weighting coefficients.

9. The electronic blue team simulation equipment similarity analysis method according to claim 8, characterized in that, This also includes a consistency check on the judgment matrix A: CR A =CI A / RI A Among them, CI A As a consistency indicator, RI A CR is the average random consistency index. A To calculate the random consistency ratio; When CR A If the value is ≤0.1, the judgment matrix A is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be corrected and the consistency check needs to be performed again.

10. A similarity analysis system for electronic blue team simulation equipment, characterized in that, include: The evaluation object determination module is used to: determine the objects for electronic blue team simulation similarity evaluation; The evaluation index system determination module is used to: determine the electronic blue team simulation similarity evaluation index system based on the electronic blue team simulation similarity evaluation object; The single-dimensional similarity calculation module is used to: perform single-dimensional similarity analysis and calculation of electronic blue team simulation based on the electronic blue team simulation similarity evaluation index system, and obtain the similarity score of the target dimension index system set; The multi-dimensional similarity calculation module is used to: perform multi-dimensional similarity analysis and calculation for electronic blue team simulation based on the similarity score of all dimension indicator system sets, and determine the similarity of electronic blue team simulation equipment; The judgment module is used to determine the accuracy of the simulation by the blue team simulation equipment based on the determined similarity of the electronic blue team simulation equipment.

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