Missile defense method and system

Abstract

The present invention discloses a missile defense method and system, belonging to the field of missile defense technology. The present invention first allocates a corresponding candidate kill chain set to each incoming missile according to its attributes; then selects a better strike node with the goal of maximizing the total hit rate of all incoming missiles, minimizing the total weapon cost used for all incoming missiles, and ensuring the consistency of the number of weapons on the strike node for each incoming missile; selects a better reconnaissance node with the goal of maximizing the total reconnaissance time for all incoming missiles and ensuring the consistency of the number of target channels of the reconnaissance node for each incoming missile, thereby optimizing the candidate kill chain set of each incoming missile, generating a first-generation population with better performance for a subsequent genetic algorithm, avoiding the generation of local optimal solutions, and dynamically and accurately adjusting the missile allocation strategy according to the real-time situation of the incoming missile, thereby improving the utilization rate of defense resources while ensuring the interception success rate.

Description

Technical Field

[0001] The present invention belongs to the field of missile defense technology, and more specifically, relates to a missile defense method and system. Background Art

[0002] With the rapid development of missile technology, it has gradually become a core weapon in modern warfare. For defenders, to avoid missile attacks, they need to effectively intercept the attacking missiles and implement anti-missile defense. This is especially true in complex aerial threat environments, where enemy missiles are diverse, fast, powerful, and may employ complex strategies such as hypersonic flight and evasive maneuvers, greatly increasing the difficulty of interception. Therefore, the research of missile defense methods and systems is of great significance.

[0003] Most existing missile defense methods rely on rules or empirical rules for missile allocation and defense. Although these methods have certain defensive capabilities, they do not fully consider the current situation and the characteristics of defense resources. They do not coordinate defense resources and conduct kill chain optimization in a timely and effective manner. As a result, they cannot reconcile the interception success rate and defense resource utilization rate. Summary of the Invention

[0004] In response to the above-mentioned deficiencies or improvement needs of the prior art, the present invention provides a missile defense method and system, the purpose of which is to improve the utilization rate of defense resources while ensuring the interception success rate.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a missile defense method, comprising:

[0006] Obtain information about incoming missiles, including the number of incoming missiles and the attributes of each incoming missile; the attributes include: the type, location, and direction of the incoming missile;

[0007] For each incoming missile, a corresponding candidate kill chain set is generated based on its attributes; the kill chain includes: reconnaissance node, control node and strike node;

[0008] Obtain a set of strike nodes for each incoming missile; the strike node set is the set consisting of all strike nodes in the candidate kill chain set corresponding to the incoming missile; select a strike node from each strike node set to form a strike plan, select a strike plan that meets the strike objective, and record the corresponding values ​​of P, V, and R, and then calculate the Nash equilibrium value of each strike node in each strike node set; the strike objectives include: simultaneously maximizing the sum of the damage probabilities P for all incoming missiles, minimizing the sum of the weapon costs V for all incoming missiles, and minimizing the variance R of the number of weapons at the strike node for each incoming missile;

[0009] Obtain a set of reconnaissance nodes for each incoming missile; the reconnaissance node set is the set consisting of all reconnaissance nodes in the candidate kill chain set corresponding to the incoming missile; select a reconnaissance node from each reconnaissance node set to form a reconnaissance plan, select the reconnaissance plan that meets the reconnaissance objectives, and record the corresponding E and Z values, and then calculate the Nash equilibrium value of each reconnaissance node in each reconnaissance node set; the reconnaissance objectives include: maximizing the sum of the reconnaissance time E for all incoming missiles and minimizing the variance Z of the number of target channels of each reconnaissance node;

[0010] For each incoming missile: select N / 2 nodes with the smallest Nash equilibrium value from its attack node set and reconnaissance node set respectively to obtain the attack node subset and reconnaissance node subset; prune the candidate kill chain set of the incoming missile, and only retain the kill chains of the attack nodes belonging to the attack node subset and the kill chains of the reconnaissance nodes belonging to the reconnaissance node subset, and calculate the Nash equilibrium value of each retained candidate kill chain; initialize the current population to the candidate kill chain set after pruning, and use the genetic algorithm to generate a new kill chain for the current population. The operation of generating a new population is repeated with the new population as the current population until the preset number of iterations is reached; the Nash equilibrium value of each kill chain of the current population is calculated and recorded in each iteration, and the kill chain corresponding to the minimum Nash equilibrium value in all iterations is assigned to the incoming missile as the optimal kill chain; the Nash equilibrium value of the kill chain is the sum of the Nash equilibrium values ​​of the attack nodes and the reconnaissance nodes on it; the fitness value used in the genetic algorithm is the inverse of the Nash equilibrium value of the kill chain; N is the preset population size;

[0011] The optimal kill chain of each incoming missile constitutes the current optimal missile allocation plan to achieve missile defense.

[0012] Further preferably, the expression of the strike target is:

[0013]

[0014]

[0015]

[0016] Where n is the number of incoming missiles; r is the total number of attack nodes after deduplication in the attack plan; m i is the number of weapons in the ith attack node after deduplication in the attack plan; i = 1, 2, …, r; Indicates whether the incoming missile is within the effective attack range of the kth weapon at the i-th strike node. If so, otherwise is the probability of damage of the kth weapon at the i-th attack node to the j-th incoming missile; v ik is the kth weapon cost of the i-th attack node; Is a decision variable, indicating whether the kth weapon of the i-th attack node attacks the j-th incoming target. If so, otherwise

[0017] Further preferably, the constraints for striking the target include:

[0018]

[0019]

[0020] Further preferably, the Nash equilibrium value of the lth strike node in the strike node set of a certain incoming missile is:

[0021]

[0022] Among them, P l is the probability of damage to the incoming missile by the lth attack node in the attack node set of a certain incoming missile; V l is the weapon cost used by the lth strike node in the strike node set of a certain incoming missile against the incoming missile; R l is the number of weapons at the lth strike node in the strike node set of a certain incoming missile.

[0023] Further preferably, the expression of the detection target is:

[0024]

[0025]

[0026] Among them, t is the number of non-repeated reconnaissance nodes in the reconnaissance plan; n is the number of incoming missiles; a gj Is the jth incoming missile within the effective targeting range of the gth reconnaissance node? If so, then a gj =1; otherwise a gj =0;z g is the target channel number of the g-th reconnaissance node, g = 1, 2, …, t.

[0027] Further preferably, the constraints of the detection target include:

[0028]

[0029] Among them, y gjis a decision variable, which represents the number of target channels provided by the g-th reconnaissance node after deduplication in the reconnaissance plan for the attack of the j-th incoming missile.

[0030] Further preferably, the Nash equilibrium value of the hth reconnaissance node in the reconnaissance node set of a certain incoming missile is:

[0031]

[0032] Among them, E h is the detection time of an incoming missile by the hth detection node in the detection node set of the incoming missile; Z h is the number of target channels of the hth reconnaissance node in the reconnaissance node set of an incoming missile.

[0033] Further preferably, the above genetic algorithm is a taboo genetic algorithm.

[0034] In a second aspect, the present invention provides a missile defense system, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor executes the method provided in the first aspect of the present invention when executing the computer program.

[0035] In a third aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute the method provided in the first aspect of the present invention.

[0036] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

[0037] 1. The present invention provides a missile defense method, which designs a dynamic allocation mechanism. First, a corresponding candidate kill chain set is allocated to each incoming missile based on its attributes. Then, a preferred strike node is selected with the goal of maximizing the total hit rate against all incoming missiles, minimizing the total weapon cost used against all incoming missiles, and ensuring consistency in the number of weapons on the strike nodes for each incoming missile. The preferred reconnaissance node is selected with the goal of maximizing the total reconnaissance time against all incoming missiles and ensuring consistency in the number of target channels for the reconnaissance nodes for each incoming missile. Thus, the candidate kill chain set for each incoming missile is optimized to generate a high-performance initial population for a subsequent genetic algorithm. This avoids the generation of local optimal solutions, achieves dynamic and accurate adjustment of the missile allocation strategy based on the real-time situation of the incoming missile, and improves the utilization rate of defense resources while ensuring the interception success rate.

[0038] 2. The missile defense method provided by the present invention can handle multiple incoming missile targets simultaneously and allocate resources based on actual conditions. By adopting a dynamic allocation mechanism, it can effectively improve the response speed when dealing with multiple targets simultaneously, and ensure the rationality of resource allocation in the multi-target situation, without causing resource overload or response delay problems. Especially in a high-intensity battlefield environment, it can deal with multiple threat targets simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of a missile defense method provided by an embodiment of the present invention;

[0040] Figure 2 A detailed execution process diagram of the missile defense method provided by an embodiment of the present invention;

[0041] Figure 3 This is a diagram showing the interception allocation results of 16 incoming missiles in uniform directions in an embodiment of the present invention;

[0042] Figure 4 This is a diagram of the interception distribution results of 32 incoming missiles in uniform air directions provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0044] In order to achieve the above objectives, firstly, Figure 1 As shown, the present invention provides a missile defense method, comprising:

[0045] 1) Obtain information about incoming missiles, including the number of incoming missiles and the attributes of each incoming missile; the attributes include: the type, location, and direction of the incoming missile;

[0046] In one alternative implementation, multiple sensors (including radar, satellites, and infrared detectors) are used to acquire key information about incoming missiles in real time, such as the number of missiles, each missile's type, flight speed, threat level, real-time location, and flight trajectory, to facilitate subsequent interception and optimization operations. This data can be processed using multi-source information fusion technology to improve its accuracy and robustness.

[0047] Through multi-source fusion, the errors of single sensor data can be effectively avoided, and the ability to accurately identify and track incoming missiles in complex combat environments can be improved.

[0048] 2) For each incoming missile, a corresponding candidate kill chain set is generated based on its attributes; the kill chain includes: reconnaissance node, control node, and strike node;

[0049] Real-time inventory of all friendly air defense resources (such as air defense missiles and unmanned aerial vehicles) status data, including the quantity, location, range, damage probability, and platform cost of each weapon. Through monitoring and calculation, friendly resources are deployed and allocated in an optimized manner to quickly respond to battlefield needs. Real-time updates ensure the rational use of resources and avoid waste or over-allocation.

[0050] Based on incoming missile information and the state of its own resources, a kill chain is dynamically generated to respond to different missile threats. Each kill chain consists of a tracking node, a control node, and a strike node. The tracking node is responsible for real-time locking onto target missiles; the control node allocates appropriate air defense resources; and the strike node conducts the actual interception of incoming missiles.

[0051] It should be noted that when generating a corresponding candidate kill chain set for each incoming missile, corresponding reconnaissance nodes and strike nodes are selected for it according to its attributes, and combined with the control node to form multiple candidate kill chains, constituting the corresponding candidate kill chain set; among them, the selected reconnaissance node satisfies that the incoming missile is within the reconnaissance range of the reconnaissance node (specifically, the position and attack direction of the incoming missile are both within the reconnaissance range of the reconnaissance node), and the selected strike node satisfies that the incoming missile is within the strike range of the strike node (specifically, the position and attack direction of the incoming missile are both within the strike range of the strike node, and the type of the incoming missile also belongs to the type of missile that the weapon loaded on the strike node can strike).

[0052] Based on the threat level, type, real-time location and trajectory of the incoming missile, it automatically determines the appropriate defense strategy, dynamically generates a kill chain for it, and adjusts the priority of each node in real time to maximize the interception success rate and resource utilization.

[0053] 3) Select the best kill chain for each incoming missile from its candidate kill chain set to form the optimal missile allocation plan to achieve missile defense;

[0054] In an optional implementation, a real number encoding method is used to represent the solution to the problem to be optimized; the total number of incoming targets is n, and the number of incoming targets of the jth attack is l j candidate kill chains, and (c1,c2,…,cn) represents a solution to the kill chain optimization problem. j (j=1,2,…,n), c j ∈[1,l j ] and c j∈Z, indicating that the jth incoming target selects the cth j If there are 8 incoming targets, the first gene in the individual code (2, 3, 4, 6, 1, 3, 5, 4) represents the selection of the second candidate kill chain for the first incoming missile.

[0055] like Figure 2 As shown, in an optional implementation manner, the process of selecting the optimal kill chain from the candidate kill chain set for each incoming missile to form the optimal missile allocation plan includes:

[0056] 3.1) Based on the candidate kill chain set of each incoming missile, two game algorithms are used as meta-games for pre-inspiration to generate excellent seeds as the initial population.

[0057] 3.2.1) Obtain a set of strike nodes for each incoming missile; the strike node set is the set consisting of all strike nodes in the candidate kill chain set corresponding to the incoming missile; select a strike node from each strike node set to form a strike plan, select the strike plan that meets the strike objective, record the corresponding values ​​of P, V, and R, and then calculate the Nash equilibrium value of each strike node in each strike node set; the strike objectives include: simultaneously maximizing the sum of the damage probabilities P for all incoming missiles, minimizing the sum of the weapon costs V for all incoming missiles, and minimizing the variance R of the number of weapons at the strike node for each incoming missile;

[0058] Obtain a set of reconnaissance nodes for each incoming missile; the reconnaissance node set is the set consisting of all reconnaissance nodes in the candidate kill chain set corresponding to the incoming missile; select a reconnaissance node from each reconnaissance node set to form a reconnaissance plan, select the reconnaissance plan that meets the reconnaissance objectives, and record the corresponding E and Z values, and then calculate the Nash equilibrium value of each reconnaissance node in each reconnaissance node set; the reconnaissance objectives include: maximizing the sum of the reconnaissance time E for all incoming missiles and minimizing the variance Z of the number of target channels of each reconnaissance node;

[0059] In an optional implementation, the expression for striking a target is:

[0060]

[0061]

[0062]

[0063] Where n is the number of incoming missiles; r is the total number of attack nodes after deduplication in the attack plan; m i is the number of weapons in the ith attack node after deduplication in the attack plan; i = 1, 2, ..., r; dikj Indicates whether the incoming missile is within the effective attack range of the kth weapon at the i-th strike node. If so, d ikj =1; otherwise d ikj =0;p ikj is the probability of damage of the kth weapon at the i-th attack node to the j-th incoming missile; v ik is the kth weapon cost of the i-th attack node; x ikj is a decision variable, indicating whether the kth weapon of the i-th attack node attacks the j-th incoming target. If so, then x ikj =1; otherwise x ikj =0.

[0064] It should be noted that by minimizing the variance of the number of weapons on the strike node for each incoming missile, the consistency of the number of weapons on the strike node for each incoming missile is ensured, thereby maximizing the residual capacity of the strike node.

[0065] Furthermore, in an optional implementation manner, the constraints for striking the target include:

[0066] Each weapon carried by each strike node can only strike one incoming missile, that is:

[0067]

[0068] The number of weapons used by each attack node is less than or equal to the number of weapons it carries, that is,

[0069]

[0070] In an optional implementation, the Nash equilibrium value of the lth strike node in the strike node set of an incoming missile is:

[0071]

[0072] Among them, P l is the probability of damage to the incoming missile by the lth attack node in the attack node set of a certain incoming missile; V l is the weapon cost used by the lth strike node in the strike node set of a certain incoming missile against the incoming missile; R l is the number of weapons at the lth strike node in the strike node set of a certain incoming missile.

[0073] In an optional implementation, the expression of the detection target is:

[0074]

[0075]

[0076] Among them, t is the number of non-repeated reconnaissance nodes in the reconnaissance plan; n is the number of incoming missiles; a gj Is the jth incoming missile within the effective targeting range of the gth reconnaissance node? If so, then a gj =1; otherwise a gj =0;z g is the target channel number of the g-th reconnaissance node, g = 1, 2, …, t.

[0077] It should be noted that by minimizing the variance of the number of target channels of each reconnaissance node, the consistency of the number of target channels of the reconnaissance node for each incoming missile is ensured, thereby maximizing the residual capacity of the reconnaissance node.

[0078] In an optional implementation, the constraint condition for detecting the target includes: the number of target channels used by each detection node is less than or equal to the number of target channels it carries, specifically:

[0079]

[0080] Among them, y gj is a decision variable, which represents the number of target channels provided by the g-th reconnaissance node after deduplication in the reconnaissance plan for the attack of the j-th incoming missile.

[0081] In an optional implementation, the Nash equilibrium value of the hth reconnaissance node in the reconnaissance node set of a certain incoming missile is:

[0082]

[0083] Among them, E h is the detection time of an incoming missile by the hth detection node in the detection node set of the incoming missile; Z h is the number of target channels of the hth reconnaissance node in the reconnaissance node set of an incoming missile.

[0084] 3.2.2) For each incoming missile, select N / 2 nodes with the smallest Nash equilibrium value from the incoming missile's attack node set and reconnaissance node set, respectively, to obtain the attack node subset and reconnaissance node subset. Then, prune the candidate kill chains for the incoming missile, retaining only the kill chains containing the attack nodes in the attack node subset and the kill chains containing the reconnaissance nodes in the reconnaissance node subset. Calculate the Nash equilibrium value of each retained candidate kill chain.

[0085] The Nash equilibrium value of the kill chain is the sum of the Nash equilibrium values ​​of the attack nodes and the reconnaissance nodes on it; N is the preset population size, and in an optional implementation method, the value is 100.

[0086] Population initialization is the first key step in the genetic algorithm, which involves generating an initial population, that is, a set of potential solutions (chromosomes). The present invention adopts a heuristic initialization method to perform pre-inspiration when generating the first generation population and pre-select the better individuals.

[0087] 3.3) For each candidate kill chain set of an incoming missile, a genetic algorithm is used to generate a new population;

[0088] Specifically, for a candidate kill chain set of an incoming missile after deletion, the operation of generating a new population using a genetic algorithm includes the following steps:

[0089] 3.3.1) Initialize the current population corresponding to the incoming missile to its candidate kill chain set after deletion;

[0090] 3.3.2) Generate a new population for the current population using a genetic algorithm;

[0091] It should be noted that the genetic algorithm used in the present invention can be any genetic algorithm, such as a basic genetic algorithm, a taboo genetic algorithm, etc., which is not limited here. Preferably, the taboo genetic algorithm is used in this embodiment, which mainly includes the following operations:

[0092] Selection: Roulette wheel selection operation, taking the inverse of the Nash equilibrium value of the kill chain as the fitness value, and selecting individuals with larger fitness values ​​with a greater probability.

[0093] Crossover: Two-point crossover method. Two cutting points are randomly generated, and the matching chromosomes are exchanged with the fragments in the cutting points to obtain new chromosomes. Specifically, the selected chromosomes are matched head to tail, and a number is randomly generated. If this number is less than the crossover probability, the two chromosomes are used as parent chromosomes to cross and produce two offspring chromosomes. The average fitness value of the parent is used as the expected level, and the fitness value of the parent chromosome is used as the taboo object. All fitness values ​​are stored in the taboo table. If the fitness value of the offspring chromosome is greater than the expected level, the offspring chromosome is retained. If the fitness value of the offspring chromosome is less than the expected level, check whether the fitness value of the offspring chromosome is in the taboo table. If it is not in the taboo table, the offspring chromosome is retained; otherwise, the best parent chromosome is selected to replace the offspring chromosome.

[0094] Mutation: Similarity is used to determine whether to perform a mutation operation. A uniform mutation method can be used to randomly generate the chromosome position to be mutated, and a random integer is used to perform basic bit mutation at that position.

[0095] It should be noted that the individuals in the above operations refer to the kill chain in the population, the chromosomes also refer to the kill chain, and the exchanged fragments refer to the nodes in the kill chain.

[0096] 3.3.3) Update the current population to the new population and repeat step 3.3.2) until the preset number of iterations M is reached; and in each iteration, calculate and record the Nash equilibrium value of each kill chain of the current population; wherein, in one optional embodiment, M is 100.

[0097] 3.3.4) Assign the kill chain corresponding to the minimum Nash equilibrium value across all iterations as the optimal kill chain to the incoming missile;

[0098] The fitness value used in genetic algorithms is the inverse of the Nash equilibrium value of the kill chain. The fitness function of a genetic algorithm, also known as the evaluation function, is a key metric used to assess the quality of individuals in the algorithm, determining the performance of each individual in the problem solution space. Through this fitness function, the genetic algorithm can measure the performance of individuals in the population and select those individuals who continue to reproduce based on their fitness.

[0099] Preferably, in each iteration, the minimum Nash equilibrium value of the individual (kill chain) in each new generation of population is found. best , and only keep the ones that satisfy NashE best The individual (kill chain) corresponding to the Nash equilibrium value whose difference is less than 2ε; where ε is the Nash equilibrium solution factor, which is 0.01 in an optional implementation manner.

[0100] 3.3) The optimal kill chain of each incoming missile is used to form the current optimal missile allocation plan to achieve missile defense.

[0101] The above operations ensure that the missile allocation plan can be continuously optimized in a complex battlefield environment by avoiding local optimal solutions, and can dynamically respond to changes in the battlefield situation.

[0102] By scheduling tracking, controlling, and striking three types of nodes, a complete missile interception process is constructed, and interception strategies are dynamically adjusted based on actual conditions. By introducing the kill chain, refined management of the missile interception process is achieved, ensuring efficient execution of interception missions from detection to final strike, maximizing interception efficiency while minimizing defense costs.

[0103] The present invention can handle multiple enemy missile targets simultaneously. Specifically, it can detect the threat level and position of each target in real time and allocate resources according to actual conditions. By adopting a dynamic allocation mechanism, it is ensured that when dealing with multiple targets at the same time, the response speed can be effectively improved, and the rationality of resource allocation in the multi-target situation is ensured, and problems such as resource overload or response delay will not occur. In particular, in a high-intensity battlefield environment, multiple threat targets can be dealt with simultaneously.

[0104] In an optional implementation, a mission report is automatically generated after each mission. The report includes key information such as missile allocation, interception success rate, cost-effectiveness, and resource consumption. Mission reports are stored in a database in real time for subsequent defense mission analysis and optimization. The generation of mission reports enables the system to continuously improve missile interception strategies and provides historical data support, helping the defense system better adjust resource allocation and mission planning.

[0105] Among them, the cost-effectiveness evaluation can evaluate the cost-effectiveness of all defense resources to ensure maximum resource utilization under limited resources. Specifically, the cost-effectiveness calculation formula is:

[0106]

[0107] Among them, P hit is the missile’s hit probability; C platform The system prioritizes the allocation of more cost-effective air defense missiles based on the calculated cost-effectiveness ratio, ensuring interception efficiency while minimizing resource waste. Through effective cost and effectiveness evaluation, the system can reduce resource waste and improve the economic efficiency of defense missions while ensuring mission success.

[0108] The present invention is applicable to various complex air defense combat scenarios, and has significant advantages in the following applications:

[0109] Aircraft carrier formation defense: In an aircraft carrier formation, the system can quickly respond to multi-target missile threats and efficiently allocate resources for interception.

[0110] Theater air defense: Facing high-density missile attacks, the system can ensure multi-tasking parallel processing and maintain efficient resource utilization.

[0111] Urban airspace defense: In urban airspace defense, the system can quickly identify threats and accurately intercept them to ensure urban safety.

[0112] In order to further illustrate the implementation effect of the present invention, the following example experiments are now given:

[0113] Suppose that during an air-to-missile defense operation, the enemy launches multiple incoming targets to attack our positions. Within our defensive positions, 32 drones serve as reconnaissance nodes, providing targeting information. Fourteen unmanned aerial vehicles (UAVs) and one destroyer serve as strike nodes, carrying out the air-to-missile defense mission. The destroyer also serves as the command and control node. The incoming targets include LRASM anti-ship missiles and Tomahawk missiles. Each UAV has a combined detection range of 10-50 km, a targeting range of 25 km, and an altitude of 1 km. Each UAV is equipped with two types of weapons: short-range and medium-range missiles. Each destroyer is equipped with three types of weapons: short-range, medium-range, and long-range missiles. The weapon configuration for each strike node is shown in Table 1, and the parameters of each weapon and their probability of damage against different incoming targets are shown in Table 2.

[0114] Table 1

[0115] Attack Node Number <![CDATA[U1~U 14 ]]> <![CDATA[U 15 ]]> Weapon Configuration <![CDATA[W1×32,W2×8]]> <![CDATA[W1×64,W2×32,W3×16]]>

[0116] Table 2

[0117] Weapon number <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> Weapon cost (millions) 3 8 10 Strike range (km) 7 30 150 LRASM anti-ship missile damage probability 0.70 0.80 0.60 Tomahawk missile damage probability 0.75 0.85 0.65

[0118] In order to verify the effectiveness of the improved taboo genetic algorithm proposed in this paper, a kill chain optimization experiment was designed. The present invention constructed three maritime air defense missile cases and conducted experimental simulations on the uniform attack mode. In the present invention, the parameter population size N is set to 100, the maximum number of iterations M is 100, and the Nash equilibrium factor ε is 0.01. The number of incoming targets is set to 16 and 32 respectively. The final experimental simulation results are as follows: Figure 3 and Figure 4 shown; among them, Figure 3 This is the interception distribution result of 16 incoming missiles in uniform air direction. Figure 4 This is a diagram showing the interception distribution results of 32 incoming missiles in uniform air directions.

[0119] The effectiveness of the present invention has been verified through the detailed description and specific implementation of the above-mentioned embodiments. First, by acquiring dynamic data on enemy missiles in real time and combining it with the state management of one's own defense resources, the system can effectively achieve precise tracking, control, and interception of enemy missiles. Second, by introducing an improved taboo genetic algorithm, the missile allocation strategy is intelligently optimized, ensuring efficient interception task allocation in complex multi-target, multi-task air defense scenarios while maximizing the cost-effectiveness of defense resources. Furthermore, the cost-effectiveness evaluation function ensures that interception tasks achieve an optimal balance between economy and effectiveness, avoiding waste of resources. Finally, the mission report generation mechanism provides data support for subsequent mission optimization, further improving the system's overall defense efficiency. Therefore, the above-mentioned embodiments verify the technical advantages and practical value of the present invention in enhancing the anti-missile capabilities of air defense systems.

[0120] In a second aspect, the present invention provides a missile defense system, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor executes the method provided in the first aspect of the present invention when executing the computer program.

[0121] Specifically, in one optional embodiment, the missile defense system includes:

[0122] The enemy missile detection module is used to obtain information about incoming missiles, including the number of incoming missiles and the attributes of each incoming missile; the attributes include: the type, location, and direction of the incoming missile;

[0123] The defense module is used to execute the method provided by the first aspect of the present invention.

[0124] Preferably, in an optional embodiment, the missile defense system further comprises:

[0125] The air defense resource management module manages the resources of its own missiles and unmanned aerial vehicles, recording information such as the quantity, type, damage probability, range, and platform cost of each defensive weapon. By updating this data in real time, the system dynamically monitors the status of each defense platform and ensures the proper allocation and use of resources.

[0126] Kill chain management module: used to generate a corresponding candidate kill chain set for each incoming missile based on its attributes; the kill chain includes: reconnaissance node, control node and strike node.

[0127] Mission Report Generation Module: This module automatically generates mission reports after each interception mission, detailing the mission execution status, including missile allocation, hit rate, cost-effectiveness, and resource consumption. This module evaluates the system's overall performance and provides an optimization basis for future interception missions. Mission reports can be stored in a database and used for subsequent mission analysis and improvement, ultimately enhancing the defense system's long-term operational effectiveness.

[0128] The relevant technical solutions are the same as the missile defense method provided in the first aspect of the present invention and will not be described in detail here.

[0129] In a third aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute the method provided in the first aspect of the present invention.

[0130] The relevant technical solutions are the same as the missile defense method provided in the first aspect of the present invention and will not be described in detail here.

[0131] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A missile defense method, characterized in that: include: Obtaining information related to incoming missiles, including the number of incoming missiles and the attributes of each incoming missile; the attributes include: the type, location, and direction of the incoming missile; For each incoming missile, a corresponding candidate kill chain set is generated based on its attributes; the kill chain includes: reconnaissance node, control node and strike node; Obtain a strike node set for each incoming missile; the strike node set is the set consisting of all strike nodes in the candidate kill chain set corresponding to the incoming missile; select a strike node from each strike node set to form a strike plan, select a strike plan that meets the strike objective, and record the corresponding values ​​of P, V, and R, and then calculate the Nash equilibrium value of each strike node in each strike node set; the strike objectives include: simultaneously maximizing the sum of the damage probabilities P for all incoming missiles, minimizing the sum of the weapon costs V for all incoming missiles, and minimizing the variance R of the number of weapons at the strike node for each incoming missile; Obtain a reconnaissance node set for each incoming missile; the reconnaissance node set is the set consisting of all reconnaissance nodes in the candidate kill chain set corresponding to the incoming missile; select a reconnaissance node from each reconnaissance node set to form a reconnaissance plan, select the reconnaissance plan that meets the reconnaissance objectives, and record the corresponding E and Z values, and then calculate the Nash equilibrium value of each reconnaissance node in each reconnaissance node set; the reconnaissance objectives include: simultaneously maximizing the sum E of the reconnaissance time for all incoming missiles and minimizing the variance Z of the number of target channels of each reconnaissance node; For each incoming missile: select N / 2 nodes with the smallest Nash equilibrium value from its attack node set and reconnaissance node set respectively to obtain the attack node subset and reconnaissance node subset; prune the candidate kill chain set of the incoming missile, and only retain the kill chains of the attack nodes belonging to the attack node subset and the kill chains of the reconnaissance nodes belonging to the reconnaissance node subset, and calculate the Nash equilibrium value of each retained candidate kill chain; initialize the current population to the candidate kill chain set after pruning, and use the genetic algorithm to generate a new seed for the current population. The operation of generating a new population is repeated, and the operation of generating a new population is further repeated iteratively using the new population as the current population until a preset number of iterations is reached; and the Nash equilibrium value of each kill chain of the current population is calculated and recorded in each iteration, and the kill chain corresponding to the minimum Nash equilibrium value in all iterations is assigned to the incoming missile as the optimal kill chain; wherein the Nash equilibrium value of the kill chain is the sum of the Nash equilibrium values ​​of the attack nodes and the reconnaissance nodes on it; the fitness value used in the genetic algorithm is the inverse of the Nash equilibrium value of the kill chain; and N is the preset population size; The optimal kill chain of each incoming missile constitutes the current optimal missile allocation plan to achieve missile defense.

2. The missile defense method according to claim 1, characterized in that: The expression of the attack target is: Where n is the number of incoming missiles; r is the total number of attack nodes after deduplication in the attack plan; m i is the number of weapons in the ith attack node after deduplication in the attack plan; i = 1, 2, …, r; Indicates whether the incoming missile is within the effective attack range of the kth weapon at the i-th strike node. If so, otherwise is the probability of damage of the kth weapon at the i-th attack node to the j-th incoming missile; v ik is the kth weapon cost of the i-th attack node; Is a decision variable, indicating whether the kth weapon of the i-th attack node attacks the j-th incoming target. If so, then otherwise 3. The missile defense method according to claim 2, characterized in that: The constraints on the strike target include:

4. The missile defense method according to any one of claims 1 to 3, characterized in that: The Nash equilibrium value of the lth attack node in the attack node set of an incoming missile is: Among them, P l is the probability of damage to the incoming missile by the lth attack node in the attack node set of a certain incoming missile; V l is the weapon cost used by the lth strike node in the strike node set of a certain incoming missile against the incoming missile; R l is the number of weapons at the lth strike node in the strike node set of an incoming missile.

5. The missile defense method according to claim 1, characterized in that: The expression of the reconnaissance target is: Among them, t is the number of non-repeated reconnaissance nodes in the reconnaissance plan; n is the number of incoming missiles; a gj Is the jth incoming missile within the effective targeting range of the gth reconnaissance node? If so, then a gj =1; otherwise a gj =0;z g is the target channel number of the g-th reconnaissance node, g = 1, 2, …, t.

6. The missile defense method according to claim 5, characterized in that: The constraints of the reconnaissance target include: Among them, y gj is a decision variable, which represents the number of target channels provided by the g-th reconnaissance node after deduplication in the reconnaissance plan for the attack of the j-th incoming missile.

7. The missile defense method according to claim 1, 5 or 6, characterized in that: The Nash equilibrium value of the hth reconnaissance node in the reconnaissance node set of an incoming missile is: Among them, E h is the detection time of an incoming missile by the hth detection node in the detection node set of the incoming missile; Z h is the number of target channels of the hth reconnaissance node in the reconnaissance node set of an incoming missile.

8. The missile defense method according to claim 1, characterized in that: The genetic algorithm is a taboo genetic algorithm.

9. A missile defense system, characterized in that: include: A memory and a processor, wherein the memory stores a computer program, and the processor executes the method according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

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