Dynamic interception change-oriented unmanned aerial vehicle cluster target allocation method

Abstract

The invention relates to a dynamic interception change-oriented unmanned aerial vehicle cluster target allocation method. The method comprises the steps of setting an initial allocation strategy according to values of unmanned aerial vehicles and targets; the loss S and the income W of target distribution of the unmanned aerial vehicle cluster are calculated according to the initial distribution strategy, and then the initial overall potential function Q0 (Ci) of the unmanned aerial vehicle cluster is calculated; the distribution strategies of all the unmanned aerial vehicles are sequentially adjusted according to the value from small to large, and whether the unmanned aerial vehicles have similar unmanned aerial vehicles meeting preset conditions or not is judged; if yes, the distribution strategy of the unmanned aerial vehicle is adjusted to be the same as the strategy of the similar unmanned aerial vehicle; and otherwise, directly allocating the unmanned aerial vehicle to the unallocated interception bomb launched by the target with high value. And recalculating the overall potential function of the unmanned aerial vehicle cluster after each adjustment so as to obtain the maximum overall potential function, and taking the distribution strategy of the unmanned aerial vehicle cluster corresponding to the maximum overall potential function as the target distribution result of the unmanned aerial vehicle cluster.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) swarm intelligence technology, and in particular to a UAV swarm target allocation method oriented to dynamic interception changes. Background Art

[0002] With the development of artificial intelligence technology, drone swarm combat has become a conventional combat mode in modern warfare. Drone swarm combat refers to multiple drones communicating with each other, sharing various information about themselves, targets and the environment, and rationally planning combat tasks to each drone after comprehensive processing of all information so that they can cooperate with each other to fight together. Such a swarm combat method can not only make up for the shortcomings of the failure of the overall combat mission caused by the failure or damage of a single drone during combat, but also meet more mission requirements to perform more complex combat tasks.

[0003] The core problem faced in UAV swarm combat is how to coordinate UAV swarms. As a key link in the coordinated execution of tasks by unmanned swarms, target allocation has been studied by a large number of scholars. It can be divided into traditional optimization algorithms, market mechanism algorithms, reinforcement learning algorithms and game algorithms. Reasonable target allocation can maximize the advantages of UAV swarms, improve task execution efficiency, avoid resource waste and repeated execution, and reduce costs. In the modeling of target allocation of UAV swarms, a large number of studies have considered various constraints in actual scenarios, and conducted research on dynamic target methods of unmanned swarms in simulated actual scenarios such as imprecise intelligence information, time-sensitive targets, communication scale, and dynamic environment.

[0004] In actual scenarios, the interception of drone strikes by targets is mostly achieved by launching interceptor missiles to destroy drones, while drone clusters can consume the target's interceptor missiles through saturation strikes using swarm tactics, thereby reducing the target's interception rate and improving the penetration effect. However, the existing target allocation method still cannot accurately reflect the dynamic constraints of the target's interception of drone strikes in actual scenarios and the emergent effect formed by each individual in the drone cluster, resulting in poor strike effects. Moreover, the interception rate of the target against the drone strike in the traditional target allocation method only considers the difference in targets, and the interception rate for the same target is a fixed value. The existing target allocation method only considers the allocation of drones to targets, and does not fully consider the allocation of interceptor missiles launched to the target, which leads to poor final strike effects. Summary of the invention

[0005] In view of the above analysis, an embodiment of the present invention aims to provide a drone cluster target allocation method for dynamic interception changes, so as to solve the problem that the existing target allocation method does not take into account the dynamic interception rate of targets against drone strikes in actual scenarios, and the emergence effect of drone clusters and the allocation of interceptor missiles cannot be reflected during target allocation, resulting in poor strike effect.

[0006] The embodiment of the present invention provides a method for allocating targets of a drone cluster facing dynamic interception changes, and sets an initial allocation strategy according to the value of the drones and targets;

[0007] According to the initial allocation strategy, the loss S and benefit W of the target allocation of the drone cluster are calculated, and then the initial overall potential function Q0(C i );

[0008] The drones are sorted in order of value from small to large, and the allocation strategy of each drone is adjusted in order of value from small to large. After each adjustment, the overall potential function of the drone cluster is recalculated to obtain the largest overall potential function. The allocation strategy of the drone cluster corresponding to the largest overall potential function is used as the target allocation result of the drone cluster.

[0009] Among them, the allocation strategy of each drone is adjusted in the following way:

[0010] Determine whether the drone has similar drones that meet preset conditions;

[0011] If yes, the allocation strategy of the drone is adjusted to the same strategy as similar drones;

[0012] Otherwise, determine whether the drone has been assigned to the target in the initial allocation strategy. If so, change its allocation strategy and no longer assign it to the target. Instead, assign the drone to the interceptor missiles of unassigned drones launched by high-value targets. Otherwise, directly assign the drone to the interceptor missiles of unassigned drones launched by high-value targets.

[0013] Furthermore, the loss S of the target allocation of the drone cluster is calculated as follows:

[0014]

[0015] Among them, M is the number of drones in the drone cluster, N is the total number of targets, and γ j ′ is the dynamic interception rate of target j to the drone cluster, U i is the value of the i-th drone, A ij is the allocation strategy of UAV i to target j,

[0016]

[0017] A ig (j) is the allocation strategy of the interceptor missile g launched by UAV i to the jth target,

[0018]

[0019] Furthermore, assuming that the drone is a suicide attack, the calculation formula for the drone cluster target allocation benefit is:

[0020]

[0021] Where N is the total number of targets, M is the number of drones in the drone cluster, and q i is the damage effect that the ith UAV can cause, γ j ′ is the dynamic interception rate of target j to the drone cluster, V j is the value of the jth target, and its value range is 0-1.

[0022] Furthermore, considering the allocation of interceptor missiles g to drone i, the dynamic interception rate of target j to drone cluster is calculated as follows:

[0023]

[0024] Among them, M is the number of drones in the drone cluster, G is the total number of interceptor missiles launched by target j, and β is the interception rate of each interceptor missile against drones.

[0025] Furthermore, assuming that the drones carry out suicide attacks, each drone has the constraint that it can only launch one attack, namely:

[0026]

[0027] Among them, A ij is the allocation strategy of UAV i to target j, A ig is the allocation strategy of UAV i to interceptor missile g, N is the total number of targets, and G is the total number of interceptor missiles launched by target j.

[0028] Furthermore, the potential function Q is calculated as:

[0029]

[0030] Among them, W i The target allocation benefit of the drone cluster after adjusting the allocation strategy for the i-th drone, S i The loss of target allocation of the UAV cluster after adjusting the allocation strategy for the i-th UAV; the potential function Q(C i ) is the overall potential function of the UAV cluster after the allocation strategy of the i-th UAV is adjusted;

[0031]

[0032] Among them, V j is the value of target j, V e =0.5, A ij is the allocation strategy of drone i to target j under the current strategy, N1 is the value V j ∈(0, 0.5] target number; N2 is the value V j ∈(0.5, 1]).

[0033] Furthermore, suppose the drones are numbered from 1 to M after being sorted in order of value from small to large;

[0034] When adjusting the allocation strategy, the drone is allocated to interceptor missiles launched by unassigned drones from high-value targets, including:

[0035] If the drone is numbered 1, assign the drone to any interceptor missile launched by the target with the highest value;

[0036] If the number of the drone is 2, then calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the highest value among the remaining interceptor missiles, and calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the second highest value among the interceptor missiles of the remaining unassigned drones, and assign the drone to the interceptor missile launched by the target corresponding to the larger overall potential function;

[0037] If the number of the drone is i, calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the highest value among the interceptor missiles of the remaining unassigned drones, and calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the targets with the second to i-th highest value among the remaining interceptor missiles, and assign the drone to the interceptor missile launched by the target corresponding to the maximum overall potential function.

[0038] Further, determining whether the drone has similar drones that meet preset conditions includes:

[0039] Determine whether there is a neighboring drone within a certain threshold range from the drone i ; If there is a neighboring drone Neighbor i , calculate the relationship between the drone i and its neighboring drones Neighbor i The similarity When the similarity When it is greater than or equal to 80%, it is considered that the drone i has a similar drone that meets the preset conditions; if there are multiple similar drones that meet the preset conditions, the drone with the highest similarity is taken as the similar drone of the current drone.

[0040] Furthermore, drone i and its neighboring drone Neighbor i The similarity calculation formula is:

[0041]

[0042] q i is the damage effect of UAV i, is the damage effect of the adjacent drones of drone i, U i The value of UAV i, Neighbori is the value of similar drones to drone i.

[0043] Furthermore, let the drones be numbered from 1 to M after being sorted in ascending order of value, and let the targets be numbered from 1 to N after being sorted in ascending order of value;

[0044] Set an initial allocation strategy based on the value of drones and targets, including:

[0045] Assign the drone numbered M to the target numbered N;

[0046] UAVs numbered M-k' are assigned to targets numbered N-k', where k' ranges from 1 to min(M,N)-1;

[0047] The allocation of drones and targets is one-to-one, and the remaining drones or targets are not allocated.

[0048] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0049] 1. The present invention provides a method for allocating targets of drone clusters with dynamic interception changes. It takes into account that in actual scenarios, the interception of drone attacks by targets is achieved by launching interceptor missiles to destroy the drones, and drone clusters can consume the target's interceptor missiles through saturation strikes using swarm tactics, thereby reducing the target's interception rate and improving the penetration effect. The fixed interception rate in traditional target allocation is improved into a dynamic interception rate, thereby improving the accuracy of the profit and loss calculation in the allocation method.

[0050] 2. The present invention establishes a target allocation method for drone clusters facing dynamic interception changes; and collects the emergent responses formed by each individual in the drone cluster to the cluster as a whole, constructs a potential function based on the gains and losses of target allocation, and constructs an allocation strategy based on the relationship between the value of the drone and the target value, so that the drone cluster target allocation strategy is more in line with the actual scenario, improves the effectiveness and accuracy of drone cluster target allocation under actual constraints, and maximizes the benefits of the allocation method and minimizes the losses.

[0051] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0053] Figure 1 This is a model diagram of a target allocation method for UAV swarms facing dynamic interception changes;

[0054] Figure 2 Flowchart of the potential function game algorithm for solving the target allocation model for a UAV cluster target allocation method for dynamic interception changes. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0056] A specific embodiment of the present invention discloses a method for allocating targets of a drone cluster facing dynamic interception changes, such as Figure 1 Specifically including steps 1-3.

[0057] Step 1: Set the initial allocation strategy according to the value of drones and targets.

[0058] Suppose the drones are numbered from 1 to M after being sorted in ascending order of value, and the targets are numbered from 1 to N after being sorted in ascending order of value;

[0059] Set an initial allocation strategy based on the value of drones and targets, including:

[0060] Assign the drone numbered M to the target numbered N;

[0061] UAVs numbered M-k' are assigned to targets numbered N-k', where k' ranges from 1 to min(M,N)-1;

[0062] The allocation of drones and targets is one-to-one, and the remaining drones or targets are not allocated.

[0063] Specifically, in the initial allocation strategy, the UAV with greater value is allocated to the target with greater value, and the UAV with less value is allocated to the target with less value. Record the allocation of UAV i to target j A ij , if UAV i is assigned to target j, A ij = 1, if drone i is not assigned to target j, A ij =0.

[0064] Step 2: Calculate the loss S and gain W of the target allocation of the drone cluster according to the initial allocation strategy, and then calculate the initial overall potential function Q0(C i ).

[0065] The loss S of the target allocation of the drone cluster is calculated as follows:

[0066]

[0067] Among them, M is the number of drones in the drone cluster, N is the total number of targets, and γ j ′ is the dynamic interception rate of target j to the drone cluster, U i is the value of the i-th drone, A ij is the allocation strategy of UAV i to target j,

[0068]

[0069] A ig (j) is the allocation strategy of the interceptor missile g launched by UAV i to the jth target,

[0070]

[0071] Specifically, when the initial allocation strategy calculates the loss S of the target allocation of the drone cluster, since the drone does not consume interceptor missiles, A ig =0, the calculation formula of the loss S of the initial target allocation of the drone cluster is:

[0072] Assuming that the drone is a suicide attack, the calculation formula for the drone cluster target allocation benefit is:

[0073]

[0074] Where N is the total number of targets, M is the number of drones in the drone cluster, and q i is the damage effect that the ith UAV can cause, γ j ′ is the dynamic interception rate of target j to the drone cluster, V j is the value of the jth target, and its value range is 0-1.

[0075] The initial allocation strategy does not consider the allocation of drone i to interceptor missile g. The dynamic interception rate calculation formula of target j to drone cluster is:

[0076] γ j ′=1-(1-β) G ,

[0077] Among them, G is the total number of interceptor missiles launched by target j, and β is the interception rate of each interceptor missile against the drone.

[0078] Assuming that the drones carry out suicide attacks, each drone has the constraint that it can only launch one attack, namely:

[0079]

[0080] Among them, A ij is the allocation strategy of UAV i to target j, and N is the total number of targets.

[0081] Specifically, the initial allocation strategy does not take into account the allocation of interceptor missiles g to UAV i. Considering that the UAVs are suicide UAVs, each UAV can only attack one of the N targets when allocated.

[0082] The potential function Q calculation formula is:

[0083]

[0084] Among them, W i The target allocation benefit of the drone cluster when allocating the i-th drone target, S i The loss of drone cluster target allocation when allocating the i-th drone target; the potential function Q(C i ) is the overall potential function of the UAV cluster when the i-th UAV target is assigned;

[0085]

[0086] Among them, V j is the value of target j, V e =0.5, A ij is the allocation of drone i to target j under the current strategy, N1 is the value V j ∈(0, 0.5] target number; N2 is the value V j ∈(0.5, 1]).

[0087] Specifically, use The potential function is dynamically adjusted according to the allocation strategy, taking into account that in actual scenarios, more attention is paid to high-value targets, and the key targets in the mission are hit, that is, even if more losses are incurred, the key targets must be hit. This is a key mission-oriented approach.

[0088] Step 3: Sort the drones according to their value from small to large, and adjust the allocation strategy of each drone in order of value from small to large. After each adjustment, recalculate the overall potential function of the drone cluster to obtain the largest overall potential function, and use the allocation strategy of the drone cluster corresponding to the largest overall potential function as the target allocation result of the drone cluster.

[0089] Among them, the allocation strategy of each drone is adjusted in the following way:

[0090] Determine whether the drone has similar drones that meet preset conditions;

[0091] If yes, the allocation strategy of the drone is adjusted to the same strategy as similar drones;

[0092] Otherwise, determine whether the drone has been assigned to the target in the initial allocation strategy. If so, change its allocation strategy and no longer assign it to the target. Instead, assign the drone to the interceptor missiles of unassigned drones launched by high-value targets. Otherwise, directly assign the drone to the interceptor missiles of unassigned drones launched by high-value targets.

[0093] Determine whether the drone has similar drones that meet preset conditions, including:

[0094] Determine whether there is a neighboring drone within a certain threshold range from the drone i ; If there is a neighboring drone Neighbor i , calculate the relationship between the drone i and its neighboring drones Neighbor i The similarity When the similarity When it is greater than or equal to 80%, it is considered that the drone i has a similar drone that meets the preset conditions; if there are multiple similar drones that meet the preset conditions, the drone with the highest similarity is taken as the similar drone of the current drone.

[0095] Drone i and its neighboring drones Neighbor i The similarity calculation formula is:

[0096]

[0097] q i is the damage effect of UAV i, is the damage effect of the adjacent drones of drone i, U i For the value of drone i, is the value of similar drones to drone i.

[0098] Specifically, in the face of drone swarms, we simulate the biological characteristics of ant colonies, bee colonies, and fish schools in nature, and further consider the emergence effect of the group, that is, the strategy changes of other drones will affect the strategy selection of drone i. Referring to the division of labor characteristics of biological populations such as ant colonies, bee colonies, and wolf packs in nature (such as strong individuals perform tasks such as transportation and hunting; fast-moving individuals perform reconnaissance tasks; and sensitive individuals perform alert tasks), the individual strategy selection of drone i will tend to choose those with similar performance, which is the drone damage effect q i and drone value U i Neighbor i This way, concentrated forces and collective combat will achieve better results. The strategy selection of drone i will be affected by its neighbor drones. i The purpose of target allocation is to maximize gains and minimize losses.

[0099] Suppose the drones are numbered from 1 to M after being sorted in ascending order of value;

[0100] When adjusting the allocation strategy, the drone is allocated to interceptor missiles launched by unassigned drones from high-value targets, including:

[0101] If the drone is numbered 1, assign the drone to any interceptor missile launched by the target with the highest value;

[0102] If the number of the drone is 2, the overall potential function of the drone cluster is calculated once for the drone to be assigned to the interceptor missile launched by the target with the highest value among the remaining interceptor missiles, and the interceptor missile launched by the target with the second highest value among the interceptor missiles assigned to the remaining unassigned drones. The allocation strategy with the larger overall potential function is selected as the adjusted allocation strategy for the drone.

[0103] If the number of the drone is i, the overall potential function of the drone cluster is calculated once for the interceptor missile launched by the target with the highest value among the interceptor missiles of the remaining unassigned drones and any interceptor missile launched by the target with the second to i-th highest value among the remaining interceptor missiles, and the allocation strategy with the largest overall potential function is selected as the adjusted allocation strategy for the drone.

[0104] Specifically, this allocation scheme can be used to make tentative allocations when the effect of the allocation strategy is uncertain, and the strategy with the largest potential function after comparison can be selected as the adjustment strategy of the drone, so that the potential function of the obtained allocation strategy can be as large as possible. The drone cluster can consume the interceptor missiles of the target through saturation strikes of swarm tactics, thereby reducing the interception rate of high-value targets, and can better penetrate and cause damage to achieve greater benefits. The drones with lower value sacrifice less losses, so the drones with lower value are allocated to the interceptor missiles launched by the high-value targets, so that the role of each drone can be maximized.

[0105] The loss S of the target allocation of the drone cluster is calculated as follows:

[0106]

[0107] Among them, M is the number of drones in the drone cluster, N is the total number of targets, and γ j ′ is the dynamic interception rate of target j to the drone cluster, U i is the value of the i-th drone, A ij is the allocation strategy of UAV i to target j,

[0108]

[0109] A ig (j) is the allocation strategy of the interceptor missile g launched by UAV i to the jth target,

[0110]

[0111] Specifically, The first term in the brackets to the right of the equal sign, A ij γ j ′U i The first term is the sum of the losses of drones assigned to targets, and the second term is the sum of the losses of drones assigned to interceptors.

[0112] The calculation formula of the target allocation benefit of the drone cluster is:

[0113]

[0114] Where N is the total number of targets, M is the number of drones in the drone cluster, and q i is the damage effect that the ith UAV can cause, γ j ′ is the dynamic interception rate of target j to the drone cluster, V j is the value of the jth target, and its value range is 0-1.

[0115] Specifically, the benefit of the drone cluster target allocation takes into account the benefit of the dynamic interception rate of the target to the drone cluster, which is more relevant to the actual scenario.

[0116] Taking into account the allocation of interceptor missiles g to drone i, the dynamic interception rate calculation formula of target j to drone cluster is:

[0117]

[0118] Among them, M is the number of drones in the drone cluster, G is the total number of interceptor missiles launched by target j, and β is the interception rate of each interceptor missile against drones.

[0119] Specifically, the fixed interception rate in traditional target allocation is improved to a dynamic interception rate, which improves the accuracy of profit and loss calculation in the allocation method.

[0120] Assuming that the drones carry out suicide attacks, each drone has the constraint that it can only launch one attack, namely:

[0121]

[0122] Among them, A ij is the allocation strategy of UAV i to target j, A ig is the allocation strategy of UAV i to interceptor missile g, N is the total number of targets, and G is the total number of interceptor missiles launched by target j.

[0123] Specifically, considering that the drones are suicide drones, each drone can only strike one of the targets or interceptor missiles when assigned.

[0124] Figure 2 Flowchart of the potential function game algorithm for solving the target allocation model for a UAV cluster target allocation method for dynamic interception changes.

[0125] Facing each drone individual i, based on game theory, it will choose the most beneficial strategy C based on itself i , thus achieving the minimum loss S at this time i (·) and the maximum benefit W i (·), where C i ={A ij ,A ig}. Finally, the largest Q(C i ) as the allocation strategy.

[0126] Compared with the prior art, the present embodiment provides a method for allocating targets of drone clusters facing dynamic interception changes. Considering that in actual scenarios, the interception of drone strikes by targets is achieved by launching interceptor missiles to destroy drones, and drone clusters can consume the interceptor missiles of targets through saturation strikes of swarm tactics, thereby reducing the interception rate of targets and improving the constraint of penetration effect. The fixed interception rate in traditional target allocation is improved to a dynamic interception rate, and the accuracy of profit and loss calculation in the allocation method is improved. The present embodiment establishes a method for allocating targets of drone clusters facing dynamic interception changes; and collects the emergent response formed by each individual in the drone cluster to the entire cluster, constructs a potential function based on the profit and loss of target allocation, and constructs an allocation strategy based on the relationship between the value of the drone and the value of the target, so that the drone cluster target allocation strategy is more in line with the actual scenario, improves the effectiveness and accuracy of drone cluster target allocation under actual constraints, and maximizes the benefits of the allocation method and minimizes the losses.

[0127] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0128] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for allocating targets of drone clusters facing dynamic interception changes, characterized in that: Set the initial allocation strategy according to the value of drones and targets; According to the initial allocation strategy, the loss S and benefit W of the target allocation of the drone cluster are calculated, and then the initial overall potential function Q0(C i ); The drones are sorted in order of value from small to large, and the allocation strategy of each drone is adjusted in order of value from small to large. After each adjustment, the overall potential function of the drone cluster is recalculated to obtain the largest overall potential function. The allocation strategy of the drone cluster corresponding to the largest overall potential function is used as the target allocation result of the drone cluster. Among them, the allocation strategy of each drone is adjusted in the following way: Determine whether the drone has similar drones that meet preset conditions; If yes, the allocation strategy of the drone is adjusted to the same strategy as similar drones; Otherwise, determine whether the drone has been assigned to the target in the initial allocation strategy. If so, change its allocation strategy and no longer assign it to the target. Instead, assign the drone to the interceptor missiles of unassigned drones launched by high-value targets. Otherwise, directly assign the drone to the interceptor missiles of unassigned drones launched by high-value targets.

2. The target allocation method according to claim 1, characterized in that: The loss S of the target allocation of the drone cluster is calculated as follows: Among them, M is the number of drones in the drone cluster, N is the total number of targets, and γ j ′ is the dynamic interception rate of target j to the drone cluster, U i is the value of the i-th drone, A ij is the allocation strategy of UAV i to target j, A ig (j) is the allocation strategy of the interceptor missile g launched by UAV i to the jth target, 3. The target allocation method according to claim 2, characterized in that: Assuming that the drone is a suicide attack, the calculation formula for the drone cluster target allocation benefit is: Where N is the total number of targets, M is the number of drones in the drone cluster, and q i is the damage effect that the ith UAV can cause, γ j ′ is the dynamic interception rate of target j to the drone cluster, V j is the value of the jth target, and its value range is 0-1.

4. The target allocation method according to claim 2 or 3, characterized in that: Taking into account the allocation of interceptor missiles g to drone i, the dynamic interception rate calculation formula of target j to drone cluster is: Among them, M is the number of drones in the drone cluster, G is the total number of interceptor missiles launched by target j, and β is the interception rate of each interceptor missile against drones.

5. The target allocation method according to claim 4, characterized in that: Assuming that the drones carry out suicide attacks, each drone has the constraint that it can only launch one attack, namely: Among them, A ij is the allocation strategy of UAV i to target j, A ig is the allocation strategy of UAV i to interceptor missile g, N is the total number of targets, and G is the total number of interceptor missiles launched by target j.

6. The target allocation method according to claim 3, characterized in that: The potential function Q calculation formula is: Among them, W i The target allocation benefit of the drone cluster after adjusting the allocation strategy for the i-th drone, S i The loss of target allocation of the UAV cluster after adjusting the allocation strategy for the i-th UAV; the potential function Q(C i ) is the overall potential function of the UAV cluster after the allocation strategy of the i-th UAV is adjusted; Among them, V j is the value of target j, V e =0.5, A ij is the allocation strategy of drone i to target j under the current strategy, N1 is the value V j ∈(0, 0.5] target number; N2 is the value V j ∈(0.5, 1]).

7. The target allocation method according to claim 1, characterized in that: Suppose the drones are numbered from 1 to M after being sorted in ascending order of value; When adjusting the allocation strategy, the drone is allocated to interceptor missiles launched by unassigned drones from high-value targets, including: If the drone is numbered 1, assign the drone to any interceptor missile launched by the target with the highest value; If the number of the drone is 2, then calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the highest value among the remaining interceptor missiles, and calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the second highest value among the interceptor missiles of the remaining unassigned drones, and assign the drone to the interceptor missile launched by the target corresponding to the larger overall potential function; If the number of the drone is i, calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the target with the highest value among the interceptor missiles of the remaining unassigned drones, and calculate the overall potential function of the drone cluster when the drone is assigned to the interceptor missile launched by the targets with the second to i-th highest value among the remaining interceptor missiles, and assign the drone to the interceptor missile launched by the target corresponding to the maximum overall potential function.

8. The target allocation method according to claim 1, characterized in that: Determine whether the drone has similar drones that meet preset conditions, including: Determine whether there is a neighboring drone within a certain threshold range from the drone i ; If there is a neighboring drone Neighbor i , calculate the relationship between the drone i and its neighboring drones Neighbor i The similarity When the similarity When it is greater than or equal to 80%, it is considered that the drone i has a similar drone that meets the preset conditions; if there are multiple similar drones that meet the preset conditions, the drone with the highest similarity is taken as the similar drone of the current drone.

9. The target allocation method according to claim 8, characterized in that: Drone i and its neighboring drones Neighbor i The similarity calculation formula is: q i is the damage effect of UAV i, is the damage effect of the adjacent drones of drone i, U i For the value of drone i, is the value of similar drones to drone i.

10. The target allocation method according to claim 1, characterized in that: Suppose the drones are numbered from 1 to M after being sorted in ascending order of value, and the targets are numbered from 1 to N after being sorted in ascending order of value; Set an initial allocation strategy based on the value of drones and targets, including: Assign the drone numbered M to the target numbered N; UAVs numbered M-k' are assigned to targets numbered N-k', where k' ranges from 1 to min(M,N)-1; The allocation of drones and targets is one-to-one, and the remaining drones or targets are not allocated.

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