Aircraft clustering cluster collaborative strike decision-making method and device

Abstract

The invention discloses an aircraft clustering cluster collaborative strike decision-making method and device, and aims to solve the collaborative strike problem of aircraft clusters in attack and defense confrontation. The method comprises the following steps: firstly, by establishing an aircraft cluster alliance cooperative game model, converting a cooperative strike problem into a cooperative game problem; secondly, making an optimal alliance cooperation strategy by using an iterative clustering algorithm oriented to cooperative alliance combat benefits, thereby maximizing the cooperative combat benefits of the cluster; and finally, determining an optimal sequential collaborative strike strategy according to the strike probability matrix so as to enhance the strike effect of the clustering cluster on the enemy target. According to the device, modular design is adopted, alliance construction and target distribution of aircraft cluster collaborative strike can be automatically achieved, and then the collaborative combat effectiveness of the aircraft cluster in a complex confrontation environment is effectively improved. The device is simple and convenient in structure and easy to implement.

Description

Technical Field

[0001] The present invention relates to the field of cluster mission planning, and in particular to a method and device for making decisions on aircraft clustering and coordinated attack. Background Art

[0002] In the modern computing environment, battlefield informatization and intelligence have become the main trend. As a new type of combat force, aircraft clusters have become an important part of the future battlefield with their flexibility, efficiency and intelligence. However, aircraft clusters often have the characteristics of a large number of nodes, fast movement speed, and frequent changes in network topology. The use of traditional global communication network structures is prone to communication delays and interference, thus affecting the effectiveness of cluster collaborative operations.

[0003] In order to meet the above challenges, clustering came into being. Clustering refers to dividing a large-scale cluster into several smaller clusters. The agents in each cluster perform tasks collaboratively, and different clusters exchange information and allocate tasks through coordination mechanisms. This architecture helps to simplify communication within the cluster and improve the stability and fault tolerance of the system. In recent years, many scholars have explored clustering methods suitable for aircraft clusters. For example, the literature (T. Ma, H. Zhou, B. Qian, and A. Fu. A large-scale clustering and 3D trajectory optimization approach for UAVswarms. Science China Information Sciences, 2021, 64: 1-16.) proposed a K-Means clustering algorithm with high efficiency and low latency for aircraft clusters to minimize the completion time of data collection tasks. The paper (MYArafat and S.Moh.Localization and clustering based on swarm intelligence in UAV networks for emergency communications.IEEE Internet of Things Journal, 2019, 6(5):8958-8976.) proposed an efficient swarm intelligence algorithm based on particle swarm optimization for clustering of aircraft clusters.

[0004] However, the above research mainly focuses on the clustering algorithm of aircraft swarms, and does not further explore the problem of coordinated strikes of clusters, while confrontation decision-making is the core of achieving cluster combat advantages. In the actual battlefield environment, in order to improve the combat effectiveness of the swarm, especially when attacking important targets, it is necessary to consider how multiple aircraft can cooperate in alliances to improve the overall combat effectiveness of the aircraft swarm. Therefore, it is of both theoretical and strategic significance to study the coordinated strike strategy of clusters to achieve alliance cooperation strikes and precision strikes. Summary of the invention

[0005] Purpose of the invention: The present invention provides a method and device for decision-making on coordinated strike of aircraft clusters, aiming to efficiently solve the problem of coordinated strike of aircraft clusters in offensive and defensive confrontation, maximize the coordinated combat efficiency of the clusters and enhance the strike effect of clusters on enemy targets.

[0006] Technical solution: In order to achieve the above invention objectives, the present invention adopts the following technical solution:

[0007] A method for aircraft clustering and coordinated attack decision-making includes the following steps:

[0008] Simulate and create an environment for aircraft swarm confrontation operations, including setting the combat areas for both sides, the number and initial position of aircraft swarms, the maximum range and safe range of weapons carried by aircraft, and enemy alliance settings;

[0009] Based on the initial position of the aircraft cluster, the value of the enemy aircraft, the maximum range and safe range of the weapons carried by the aircraft, the coordinated strike problem is transformed into a cooperative game problem, including establishing a i Attack enemy aircraft j The profit index function f ij , establish our q aircraft to cooperate to attack the enemy aircraft b j The profit indicator function Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster;

[0010] According to the cooperative game problem, the optimal alliance cooperation strategy is formulated to maximize the collaborative combat benefits of the cluster; the optimal alliance cooperation strategy is based on the initial alliance cooperation strategy R A (0), by solving the attack target strategy R that maximizes the value benefit function f of our aircraft cluster attacking the enemy aircraft cluster A (N A ) to be determined;

[0011] Based on the optimal alliance cooperation strategy and the priority of target selection, the strike probability matrix of our aircraft is constructed to determine the optimal sequential coordinated strike strategy for clusters.

[0012] An aircraft clustering and grouping coordinated attack decision device comprises: a scenario construction module, a model building module, a clustering decision module and an attack decision module;

[0013] The scenario building module is used to simulate and create an environment for aircraft cluster confrontation operations, including setting the combat areas of the enemy and our side, the number and initial position of the aircraft cluster, the maximum range and safe range of the weapons carried by the aircraft, and the enemy alliance settings;

[0014] The model building module is used to transform the coordinated strike problem into a cooperative game problem based on the initial position of the aircraft cluster, the value of the enemy aircraft, the maximum range and safe range of the weapons carried by the aircraft, including establishing a i Attack enemy aircraft j The profit index function f ij , establish our q aircraft to cooperate to attack the enemy aircraft b j The profit indicator function Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster;

[0015] The clustering decision module is used to formulate an optimal alliance cooperation strategy based on the cooperative game problem to maximize the collaborative combat benefits of the cluster; the optimal alliance cooperation strategy is based on the initial alliance cooperation strategy R A (0), by solving the attack target strategy R that maximizes the value benefit function f of our aircraft cluster attacking the enemy aircraft cluster A (N A ) to be determined;

[0016] The strike decision module is used to construct a strike probability matrix of our aircraft based on the optimal alliance cooperation strategy and strike target selection priority, and determine the optimal sequential coordinated strike strategy for clustering.

[0017] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the aircraft clustering and coordinated strike decision-making method as described above are implemented.

[0018] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned aircraft clustering and coordinated strike decision-making method.

[0019] The beneficial effects of the present invention are as follows: the present invention transforms the problem of coordinated strike into a cooperative game problem by constructing an aircraft cluster alliance cooperative game model, and designs an iterative clustering algorithm guided by the combat benefits of the cooperative alliance; the algorithm can effectively solve the optimal alliance cooperation strategy, thereby maximizing the coordinated combat benefits of the cluster; further, the optimal sequential coordinated strike strategy is determined based on the strike probability matrix of the optimal alliance cooperation strategy to enhance the strike effect of the clustering cluster on enemy targets. In addition, the device adopts a modular design, which can automatically realize the alliance construction and target allocation of the coordinated strike of the aircraft cluster, thereby effectively improving the coordinated combat effectiveness of the aircraft cluster in a complex confrontation environment. Therefore, the present invention is relatively simple in structure and easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0021] Figure 2 This is a schematic diagram of the initial position of the enemy aircraft randomly generated in the present invention.

[0022] Figure 3 This is a schematic diagram of the initial position randomly generated by our aircraft in the present invention.

[0023] Figure 4 , Figure 5 Schematic diagram of the optimal alliance cooperation strategy of our aircraft cluster in an embodiment of the present invention.

[0024] Figure 6-Figure 15 It is a schematic diagram of the sequential coordinated attack strategy of our aircraft cluster in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to have a clearer understanding of the features and advantages of the technical solution of the present invention, the composition and implementation of the specific solution are explained below in conjunction with the accompanying drawings.

[0026] The present invention provides a method for decision-making on aircraft clustering and coordinated attack, referring to Figure 1 , the method comprises the following steps:

[0027] Step 1: Establish an attack and defense confrontation scenario between the enemy and our aircraft clusters, and randomly generate the initial position of the aircraft cluster.

[0028] The specific scenario of establishing an offensive and defensive confrontation between enemy and our aircraft clusters is as follows: In a specific combat airspace Q, our aircraft cluster is performing a strike mission against the enemy aircraft cluster. Assume that there is a combat line in the combat airspace Q, dividing the combat area into our combat area Q A Fighting the enemy in area Q B The aircraft of both sides are restricted to their respective areas and cannot cross the battle line into the other side's combat area, and all aircraft perform their missions at the same flight altitude.

[0029] The enemy aircraft cluster adopts the tactical deployment of cooperative alliance, and realizes the optimal allocation of resources and flexible application of tactics by building a circular area with the alliance center as the core. B M alliance centers are randomly set in the circle, and N alliance centers are randomly distributed in the circular area with radius r and each alliance center as the center. S Aircraft designed to form multiple coordinated defense and attack alliances Let the alliance center set be S = {S1,…,S m ,…,S M}, the enemy aircraft set is The initial position of the aircraft bj is recorded as N B =MN S Indicates the number of enemy aircraft. Enemy aircraft b j The value of j , which is related to the aircraft's mission, performance, load, tactical position and other factors. Our aircraft set is recorded as The aircraft a i The initial position of N A Indicates the number of our aircraft. In addition, it is assumed that the weapons carried by each aircraft have the same maximum range d max With safe range d min .

[0030] Step 2: Assume that our aircraft cluster can obtain the location, performance, and payload of the enemy aircraft cluster through situational awareness, radar detection, and other means, and use this data to evaluate the value of the enemy aircraft. Based on the initial location of both aircraft clusters, the value of the enemy aircraft, the maximum range and safe range of the weapons carried by the aircraft, and other combat information, establish an aircraft cluster alliance cooperation game model.

[0031] The specific steps include:

[0032] Step 21: Build our aircraft a i Attack enemy aircraft j The profit index function fij ;

[0033] According to the initial positions of the enemy and our aircraft, the enemy aircraft value and the maximum range of the aircraft weapons max With safe range d min , define our aircraft a i Attack enemy aircraft j The profit index function f ij for:

[0034]

[0035] Where i = 1,…,N A ,j=1,…,N B , N A and N B are the number of our and enemy aircraft respectively; v j Indicates enemy aircraft b j The value of v max represents the maximum value in the enemy aircraft cluster B, that is, p ij For our aircraft a i Destroy enemy aircraft j The probability of is:

[0036]

[0037] Among them, d ij For our aircraft a i and target j, i.e. enemy aircraft b j When the distance d ij The closer to the safe range d min When the probability of destruction is p ij The higher the return index function f ij The bigger.

[0038] Step 22: Establish cooperation between our q aircraft to attack enemy aircraft b j The profit indicator function

[0039] Our q aircraft cooperate to attack the enemy aircraft b at the same time j The profit indicator function Defined as:

[0040]

[0041] Among them, r>1 is the cooperation coefficient, which depends on the combat capability of our q aircraft and the enemy aircraft b. jSpecifically, the larger the cooperation coefficient r, the stronger the cooperative combat capability of our q aircraft or the stronger the enemy aircraft b. j By adjusting r, we can simulate and analyze the strike effects under different combat conditions to optimize clustering strategies and strike resource allocation.

[0042] Step 23: Construct the cooperative alliance combat benefit function f of our aircraft cluster.

[0043] The cooperative alliance combat profit function f of our aircraft cluster A can be established as:

[0044]

[0045] Among them, f j B is used to attack enemy aircrafts for our aircraft j The value-benefit function of is:

[0046]

[0047] Among them, α j ∈{0,1},j=1,…,N B , by adjusting α j The combat benefits of the cooperative alliance under different attack mode combinations of our aircraft cluster can be calculated. j =0, indicating that our side has only one aircraft a i Attack enemy aircraft j ; When α j =1, indicating that our aircraft q cooperate to attack the enemy aircraft b j .

[0048] Step 3: Design an iterative clustering algorithm guided by the combat benefits of cooperative alliances to solve the optimal alliance cooperation strategy of our aircraft cluster.

[0049] The specific steps include:

[0050] Step 31: Initialize alliance cooperation strategy;

[0051] Define aircraft a i Strike Alliance Center S m The value-benefit function for:

[0052]

[0053] in, Indicates the enemy alliance center S m The value of represents the maximum value in the enemy alliance center set S, that is, Indicates our aircraft a i Destroy the enemy alliance center S m By solving the value-benefit function The biggest target Right now:

[0054]

[0055] Initialize our aircraft a i The target of the attack is the enemy alliance center Similarly, the remaining aircraft on our side all choose the enemy alliance center that can maximize their value benefits as the attack target according to the above steps. According to the attack target selected by the aircraft, the aircraft attacking the same alliance center will form an alliance, thus generating the initial alliance cooperation strategy of our aircraft cluster

[0056] Step 32: Update the alliance cooperation strategy;

[0057] For any number of iterations t∈{1,…,N A}, select candidate aircraft set A t-1 An aircraft in In particular, when the iteration number t = 1, the candidate aircraft set Given the alliance cooperation strategy of the t-1th iteration and Define the strategy space H(t) = {h1(t),…,h m (t),…,h M (t)}, where h m (t) represents aircraft a i From the current alliance Remove and join a new alliance The feasible strategies formed. According to the definition of the cooperative alliance combat benefit function f mentioned above, the calculation of m (t) under the combat benefit f(h m (t)) and choose the strategy that maximizes the combat benefit As the alliance cooperation strategy R of the tth round iteration A (t). In addition, update the candidate aircraft set A t =A t-1 \a i , to ensure that the selected aircraft is different in each iteration.

[0058] Step 33, solving the optimal alliance cooperation strategy;

[0059] After N AThe optimal alliance cooperation strategy of our aircraft cluster is determined as in Represents Alliance of aircraft, this strategy maximizes the combat benefits of the cooperative alliance.

[0060] Step 4: Based on our aircraft strike probability matrix, formulate a cluster-based sequential coordinated strike strategy.

[0061] The specific steps include:

[0062] Step 41: Establishing the priority of selecting the strike targets;

[0063] First calculate our alliance Each aircraft strikes the enemy alliance center S m The probability of Sort them from high to low according to the probability of attack; finally, generate an alliance based on the sorting results The priority of target selection for medium aircraft

[0064] Step 42, initializing the strike probability matrix;

[0065] According to the optimal alliance cooperation strategy R A (N A ) and target selection priority Construct the attack probability matrix P for each alliance separately m (0),m∈{1,…,M}, that is

[0066]

[0067] Among them, p ij ,i∈{T1,…,TN m},j∈{1,…,N S} indicates our alliance Medium Aircraft i Destroy the enemy alliance Medium aircraft b j probability.

[0068] Step 43, select the target to attack;

[0069] Based on the priority determined in step 41 The highest priority aircraft a T1 First, according to the attack probability matrix P m The first row of (0) selects the enemy aircraft As the target of attack. If the selected enemy aircraft By transforming the hit probability matrix Pm (0) where the first column is set to 0 and the attack probability matrix P is updated m (1), that is

[0070]

[0071] At the same time, update the alliance Sequential coordinated attack strategy Ω m (1) = {b l ,0,…,0}. Then the aircraft with the second highest priority selects the next strike target and updates the strike probability matrix and sequential coordinated strike strategy, and repeats this process until all aircraft have completed the selection of strike targets.

[0072] In particular, when the aircraft When selecting a target to attack, if the attack probability matrix P m The elements in the kth row of (k-1) are all 0, that is p Tkj = 0, then define a target set J that satisfies a preset attack probability threshold τ≤1 k = {b j |0<p Tkj <τ}, where the preset strike probability threshold τ is used to evaluate whether the target is effectively struck. If the target's strike probability exceeds the set threshold τ, it indicates that the target aircraft has basically lost its combat capability. According to the initial attack probability matrix P m (0)Select enemy aircraft As the target of attack, otherwise no target is selected. This method sets the priority With the threshold τ, the strike resource allocation can be further optimized, thereby enhancing the coordinated strike effect on enemy targets.

[0073] MATLAB 2022b is used as simulation software to simulate the attack and defense confrontation scenario of aircraft clusters. The effectiveness of the present invention is evaluated by solving the optimal alliance cooperation strategy and sequential coordinated strike strategy of our aircraft cluster, and the combat effectiveness of the cluster coordinated strike of the present invention and the combat effectiveness of the aircraft performing the strike mission alone are simulated and compared. The parameter settings of the attack and defense confrontation scenario of aircraft clusters in the simulation include: Assuming that the effective combat area Q of our aircraft cluster is A =[0,100]×[0,45), the enemy's combat area is Q B =[0,100]×(55,100]. The enemy can B N is randomly distributed in a circular area with a radius of r and the center of each alliance. S = 12 aircraft, forming 10 coordinated defense and attack alliances, with a total of N B= 120 aircraft. The initial position of the enemy aircraft cluster is as follows: Figure 2 As shown. We have N A = 120 aircraft, with weapons of maximum range d max The length of the unit is 15, and the safe range is d min is 8 units long. The initial position of our aircraft cluster is as follows Figure 3 shown. Figure 4 and Figure 5 This is a schematic diagram of the 10 optimal alliance cooperation strategies formed by our aircraft cluster based on the locations of enemy aircraft and alliance centers as well as mission requirements. Figure 4 This is the optimal alliance cooperation strategy for our aircraft to attack enemy alliances 1 to 5. Circles of the same color in our effective combat area represent clusters of aircraft belonging to the same alliance, which are responsible for attacking enemy alliances of the corresponding color. For example, the red circle represents our aircraft alliance 1, whose mission is to attack aircraft in enemy alliance 1. The same is true for other colors, corresponding to enemy alliances 2 to 5. Figure 5 The optimal alliance cooperation strategy for our aircraft to attack enemy alliances 6 to 10 is formulated by an iterative clustering algorithm guided by the cooperative alliance combat benefits of the present invention. A (N A ). According to the optimal alliance cooperation strategy R A (N A ), a cluster-based sequential coordinated attack strategy Ω={Ω1,…,Ω 10}. Figures 6 to 15 The specific attack strategies of our 10 clusters are shown respectively, and the arrows indicate the attack relationship between our aircraft and the enemy aircraft. Figure 6 Each aircraft in our alliance 1 points to an enemy aircraft through an arrow, indicating that these aircraft have selected the enemy aircraft being pointed at as their attack target. If an aircraft in our alliance does not point to any enemy aircraft through an arrow (such as Figure 8 ), it means that the aircraft has not been assigned any strike mission. This is because its expected strike effect is poor, or its expected target has been selected by an aircraft with a higher priority and has been effectively struck, that is, the probability of the expected target being struck is greater than the preset strike probability threshold τ = 0.8. This method can optimize the configuration of strike resources, thereby enhancing the coordinated strike effect on enemy targets.

[0074] In order to better demonstrate the combat effectiveness of the cluster coordinated strike system of the present invention, the strike mission execution efficiency index is defined as: Among them, f* represents the optimal alliance cooperation strategy R A (N A ) and the cooperative alliance combat benefits under the sequential coordinated strike strategy Ω; Indicates that the aircraft does not cooperate with other aircraft, and each aircraft selects the enemy aircraft with the highest attack probability as the attack target to obtain the total target value. To ensure the robustness of the results, the initial position of our aircraft cluster is randomized and the simulation program is run 100 times. The average task execution efficiency index can be obtained as Compared with an aircraft performing a strike mission individually, the present invention can effectively solve the problem of coordinated strikes by aircraft clusters in offensive and defensive confrontations, improve the coordinated combat efficiency of the cluster, and enhance the cluster's strike effect on enemy targets.

[0075] Based on the same technical concept as the method embodiment, the present invention also provides an aircraft clustering and coordinated attack decision-making device, including: a scenario construction module, a model building module, a clustering decision module and an attack decision module;

[0076] The scenario building module is used to simulate and create an environment for aircraft cluster confrontation operations, including setting the combat areas of the enemy and our side, the number and initial position of the aircraft cluster, the maximum range and safe range of the weapons carried by the aircraft, and the enemy alliance settings;

[0077] The model building module is used to transform the coordinated strike problem into a cooperative game problem based on the initial position of the aircraft cluster, the value of the enemy aircraft, the maximum range and safe range of the weapons carried by the aircraft, including establishing a i Attack enemy aircraft j The profit index function f ij , establish our q aircraft to cooperate to attack the enemy aircraft b j The profit indicator function Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster;

[0078] The clustering decision module is used to formulate an optimal alliance cooperation strategy based on the cooperative game problem to maximize the collaborative combat benefits of the cluster; the optimal alliance cooperation strategy is based on the initial alliance cooperation strategy R A (0), by solving the attack target strategy R that maximizes the value benefit function f of our aircraft cluster attacking the enemy aircraft cluster A (N A ) to be determined;

[0079] The strike decision module is used to construct a strike probability matrix of our aircraft based on the optimal alliance cooperation strategy and strike target selection priority, and determine the optimal sequential coordinated strike strategy for clustering.

[0080] It should be understood that the aircraft clustering and coordinated strike decision-making device in the embodiment of the present invention can implement all the technical solutions in the above-mentioned method embodiment, and the functions of its various functional modules can be specifically implemented according to the methods in the above-mentioned method embodiments. The specific implementation process can refer to the relevant description in the above-mentioned embodiments, which will not be repeated here.

[0081] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the aircraft clustering and coordinated strike decision-making method as described above are implemented.

[0082] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned aircraft clustering and coordinated strike decision-making method.

[0083] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices (systems), computer equipment or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0084] The present invention is described with reference to a flowchart of a method according to an embodiment of the present invention. It should be understood that each process in the flowchart and a combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A device that specifies functions in a process or multiple processes.

[0085] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 The steps of a specified function in a process or multiple processes.

Claims

1. A method for decision-making on aircraft clustering and coordinated attack, characterized in that: The following steps are involved: Simulate and create an environment for aircraft swarm confrontation operations, including setting the combat areas for both sides, the number and initial position of aircraft swarms, the maximum range and safe range of weapons carried by aircraft, and enemy alliance settings; Based on the initial position of the aircraft cluster, the value of the enemy aircraft, the maximum range and safe range of the aircraft's weapons, the coordinated strike problem is transformed into a cooperative game problem, including establishing a i Strike enemy aircraft j The profit index function f ij , establish our q aircraft to cooperate to attack the enemy aircraft b j The profit indicator function Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster; According to the cooperative game problem, the optimal alliance cooperation strategy is formulated to maximize the collaborative combat benefits of the cluster; the optimal alliance cooperation strategy is based on the initial alliance cooperation strategy R A (0), by solving the attack target strategy R that maximizes the value benefit function f of our aircraft cluster attacking the enemy aircraft cluster A (N A ) to be determined; Based on the optimal alliance cooperation strategy and the priority of target selection, the strike probability matrix of our aircraft is constructed to determine the optimal sequential coordinated strike strategy for clusters.

2. The method according to claim 1, characterized in that: Build our aircraft a i Strike enemy aircraft j The profit index function f ij ,include: According to the initial positions of the enemy and our aircraft, the enemy aircraft value and the maximum range of the aircraft weapons max With safe range d min , define our aircraft a i Strike enemy aircraft j The profit index function f ij for: Where i = 1,…,N A ,j=1,…,N B , N A and N B are the number of our and enemy aircraft respectively; v j Indicates enemy aircraft b j The value of v max represents the maximum value in the enemy aircraft cluster B, that is, p ij For our aircraft a i Destroy enemy aircraft j The probability of is: Among them, d ij For our aircraft a i and target j, i.e. enemy aircraft b j The distance between them, when the distance d ij The closer to the safe range d min When the probability of destruction is p ij The higher the return index function f ij The bigger.

3. The method according to claim 2, characterized in that Our q aircraft cooperate to attack the enemy aircraft b at the same time j The profit indicator function Defined as: Among them, r>1 is the cooperation coefficient, which depends on the combat capability of our q aircraft and the enemy aircraft b. j The larger the cooperation coefficient r, the stronger the cooperative combat capability of our q aircraft or the stronger the enemy aircraft b j The weaker the defense capability.

4. The method according to claim 3, characterized in that Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster, including: The cooperative alliance combat profit function f of our aircraft cluster A is established as: Among them, f j B is used to attack enemy aircrafts for our aircraft j The value-benefit function of is: Among them, α j ∈{0,1},j=1,…,N B , by adjusting α j It can calculate the cooperative alliance combat benefits of our aircraft cluster under different attack mode combinations. j =0, indicating that our side has only one aircraft a i Strike enemy aircraft j ; When α j =1, indicating that our aircraft q cooperate to attack the enemy aircraft b j .

5. The method according to claim 1, characterized in that: Formulating the optimal alliance cooperation strategy specifically includes: Step 31: Initialize alliance cooperation strategy; Define aircraft a i Strike the enemy alliance center S m The value-benefit function for: in, Indicates the enemy alliance center S m The value of represents the maximum value in the enemy alliance center set S, that is, Indicates our aircraft a i Destroy the enemy alliance center S m The probability of The biggest target Right now: Initialize our aircraft a i The target of the attack is the enemy alliance center The remaining aircraft of our side select the enemy alliance center that can maximize its value benefit as the attack target according to the above steps; according to the attack target selected by the aircraft, the aircraft that attack the same alliance center will form an alliance, thus generating the initial alliance cooperation strategy of our aircraft cluster Step 32: Update the alliance cooperation strategy; For any number of iterations t∈{1,…,N A }, select candidate aircraft set A t-1 An aircraft in Perform strike strategy redeployment, where when the iteration number t = 1, the candidate aircraft set Given the alliance cooperation strategy of the t-1th iteration and Define the strategy space H(t) = {h1(t),…,h m (t),…,h M (t)}, where h m (t) represents aircraft a i From the current alliance Remove and join a new alliance The feasible strategies formed; according to the definition of the cooperative alliance combat benefit function f, calculate the m (t) under the combat benefit f(h m (t)) and choose the strategy that maximizes the combat benefit As the alliance cooperation strategy R of the tth round iteration A (t); Update the candidate aircraft set A t =A t-1 \a i , to ensure that the selected aircraft is different in each iteration; Step 33, solving the optimal alliance cooperation strategy; After N A The optimal alliance cooperation strategy of our aircraft cluster is determined as in Represents Alliance of aircraft, this strategy maximizes the combat benefits of the cooperative alliance.

6. The method according to claim 1, characterized in that The priority of target selection is determined according to the following method: First calculate our alliance Each aircraft strikes the enemy alliance center S m The probability of Sort them from high to low according to the probability of attack; finally, generate an alliance based on the sorting results The priority of target selection for medium aircraft 7. The method according to claim 6, characterized in that Based on the optimal alliance cooperation strategy and the priority of target selection, we build a probability matrix for our aircraft strike and determine the optimal sequential coordinated strike strategy for clusters, including: Step 41: According to the optimal alliance cooperation strategy R A (N A ) and target selection priority Construct the attack probability matrix P for each alliance separately m (0),m∈{1,…,M}, we have: Among them, p ij ,i∈{T1,…,TN m },j∈{1,…,N S } indicates our alliance Medium Aircraft i Destroy the enemy alliance Medium aircraft b j probability; Step 42: Based on the determined priority The highest priority aircraft a T1 First, according to the attack probability matrix P m The first row of (0) selects the enemy aircraft As a target, if the selected enemy aircraft By transforming the hit probability matrix P m (0) where the first column is set to 0 and the attack probability matrix P is updated m (1) , we have: At the same time, update the alliance Sequential coordinated attack strategy Ω m (1) = {b l ,0,…,0}; then the aircraft with the second highest priority selects the next attack target and updates the attack probability matrix and sequential coordinated attack strategy, and repeats this process until all aircraft have completed the selection of attack targets.

8. An aircraft clustering and grouping coordinated attack decision-making device, characterized in that: include: The scenario building module is used to simulate and create an environment for aircraft cluster confrontation operations, including setting the combat areas of the enemy and our side, the number and initial position of the aircraft cluster, the maximum range and safe range of the weapons carried by the aircraft, and the enemy alliance settings; The model building module is used to transform the coordinated strike problem into a cooperative game problem based on the initial position of the aircraft cluster, the value of the enemy aircraft, the maximum range and safe range of the aircraft's weapons, including the establishment of our aircraft a i Strike enemy aircraft j The profit index function f ij , establish our q aircraft to cooperate to attack the enemy aircraft b j The profit indicator function Joint ij and Construct the cooperative alliance combat benefit function f of our aircraft cluster; The clustering decision module is used to formulate the optimal alliance cooperation strategy according to the cooperative game problem to maximize the collaborative combat efficiency of the cluster; the optimal alliance cooperation strategy is based on the initial alliance cooperation strategy R A (0), by solving the attack target strategy R that maximizes the value benefit function f of our aircraft cluster attacking the enemy aircraft cluster A (N A ) to be determined; The strike decision module is used to construct the strike probability matrix of our aircraft based on the optimal alliance cooperation strategy and the strike target selection priority, and determine the optimal sequential coordinated strike strategy for clusters.

9. A computer device, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the aircraft clustering and coordinated strike decision-making method as described in any one of claims 1-7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the aircraft clustering and coordinated attack decision-making method as described in any one of claims 1 to 7 are implemented.

Images