A Passive Defense-Based Method for Intercepting Unmanned Surface Vessel Swarms

Abstract

This invention relates to a passive defense-based unmanned surface vessel (USV) swarm interception method, comprising the following steps: establishing motion models of the defending and attacking USVs based on the speed and maneuverability differences between the defender and attacker; defining the strike radius and defense radius, where objects approaching within the USV's strike radius will be destroyed; the defense radius being the distance between the defending USV and the target point; predicting the path of the attacking USV using a passive defense method; assigning task targets to the defending USV swarm using a heuristic task allocation search algorithm; the attacking USV employing an improved artificial potential field method for path planning and dynamic obstacle avoidance to evade the interception by the defending USVs; and evaluating the USV swarm interception effectiveness based on multiple interception effectiveness evaluation indicators. Compared with existing technologies, this invention can utilize the swarm advantage and positional advantage of the defender to compensate for its speed disadvantage, thus better executing the interception mission.

Description

Technical Field

[0001] This invention relates to the field of intelligent control, and in particular to a method for intercepting unmanned surface vessel swarms based on passive defense. Background Technology

[0002] As human society's pursuit of economic development becomes increasingly multi-dimensional and comprehensive, the ocean, with its abundant natural resources and research value, has become a crucial strategic space for countries worldwide. Unmanned surface vessels (USVs), as small to medium-sized surface platforms capable of autonomous navigation, mitigating the risk of human casualties, and widely applied in various missions, are crucial. Civilian USVs can handle search, exploration, and hydrographic surveys in rivers, lakes, and seas, while military USVs can be equipped with more advanced sensors and weapon systems to address more complex and diverse tasks such as patrol, navigation, assault, and anti-submarine warfare.

[0003] However, tracking and interception methods based on encirclement and suppression only achieve good interception results when the attacker's speed is lower than the defender's. When the defender's unmanned surface vessel (USV) is slower and less maneuverable than the attacker's, the interception success rate is almost zero. In other words, existing USV swarm coordination interception methods do not consider the speed difference between the attacker and defender, making it difficult to achieve effective interception when the defender's speed is lower than the attacker's. Summary of the Invention

[0004] The purpose of this invention is to provide a method for intercepting unmanned surface vessel swarms based on passive defense.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] A passive defense-based method for intercepting unmanned surface vessel (USV) swarms includes the following steps:

[0007] S1. Based on the speed and maneuverability differences between the defender and the attacker, establish motion models for the unmanned surface vessels of the defender and the attacker.

[0008] S2 defines the strike radius and defense radius. Objects approaching the strike radius of the unmanned surface vessel will be destroyed. The defense radius is the distance between the defending unmanned surface vessel and the target point. The passive defense method is used to predict the path of the attacking unmanned surface vessel, and a heuristic task allocation search algorithm is used to allocate task targets to the defending unmanned surface vessel cluster.

[0009] S3, the attacking unmanned surface vessel uses an improved artificial potential field method for path planning and dynamic obstacle avoidance to avoid the interception of the defending unmanned surface vessel;

[0010] S4 evaluates the interception effect of the unmanned surface vessel swarm based on multiple interception effect evaluation indicators.

[0011] The motion model of the defending and attacking unmanned surface vessels is as follows: For unmanned surface vessel i, its position at time t is (x... i (t),y i (t)), where longitudinal velocity and heading are respectively expressed as v. i (t) and θ i (t), then according to the principles of kinematics, calculate the position of the unmanned surface vessel at the next moment t+Δt:

[0012]

[0013] When the defender's speed and maneuverability are lower than the attacker's, the defender's unmanned surface vessels (USVs) do not take the initiative to attack, but instead choose to defend passively. Based on the general direction of the attacker's USV movement, which will inevitably be towards the target point, the defender's USV swarm forms a defensive ring within the defensive radius, waiting for the opponent's attack.

[0014] Step S2 specifically involves: for the attacking unmanned surface vessel, the distance to the target point is R. a The speed is v a For the defending unmanned surface vessel, the defense radius is R. d The speed is v d And v d <v a During the engagement between the attacking and defending unmanned surface vessels (USVs), their trajectories are considered as concentric circles centered on the target point, with radii R and R, respectively. a and R d To ensure that there is always a defending unmanned surface vessel on the line connecting the attacker and the target point, the following should be true:

[0015]

[0016] Based on the determined defense radius, task target points are selected evenly on the concentric circles, and task points are assigned to the unmanned surface vessel cluster using a heuristic task allocation search algorithm to execute the encirclement and interception task.

[0017] For a swarm of N unmanned surface vessels (USVs), the defender uses a heuristic task assignment search algorithm based on known information to assign each of the N USVs to one of the N target points obtained from the predictive interception method. The heuristic task assignment search algorithm is specifically as follows:

[0018] The defending unmanned surface vessel cluster is denoted as set. The task objectives are denoted as set. The mission objective of unmanned surface vessel i is denoted as q. i The task allocation for the entire unmanned surface vessel swarm is denoted as Q = q1,...,q NFor each unmanned surface vessel i, calculate the distance dis(i,s) between it and each mission objective:

[0019]

[0020] Using the center of the unmanned surface vessel (USV) swarm as a reference, the distance between each individual in the swarm and the swarm center is used as the standard for measuring the relative position of the individual. Using the center of the mission objective point as a reference, the distance between each mission objective point and the mission objective point center is used as the standard for measuring the relative position of the mission objective point. After reordering the individuals and mission objective points from nearest to farthest, a heuristic search is then used. The search formula is as follows:

[0021]

[0022] Where f1(i) represents the distance sorted of the unmanned surface vessel numbered i from the center of the unmanned surface vessel cluster, and f2(s) represents the distance sorted of the mission target point numbered s from the center of the mission target point among all mission targets.

[0023] The improved artificial potential field method specifically involves setting an artificial potential field function to guide the movement of the unmanned surface vessel. The artificial potential field function includes an attractive potential field and a repulsive potential field. The repulsive potential field is improved for dynamic obstacles. At the same time, in order to avoid the situation where the net repulsive force and the attractive force are collinear, a fictitious small perturbation repulsive force is introduced to break the equilibrium point.

[0024] The improved repulsive potential field for dynamic obstacles specifically refers to:

[0025] Based on the relationship between the repulsive potential energy intensity and the distance between the unmanned surface vessel and the obstacle, as well as the speed of the obstacle, the repulsive potential field is improved as follows:

[0026]

[0027] Among them, X i X j k represents the position of the unmanned surface vessel and the position of the obstacle, respectively. req ρ(X) is the repulsive gain coefficient. j ,X i Let ρ be the vector pointing from the location of the obstacle to the location of the unmanned surface vessel. o Let be a constant, representing the maximum distance at which the obstacle exerts a repulsive force on the unmanned surface vessel (USV), p be the direction vector from the defending USV to the attacking USV, and v be a constant. a,max This represents the maximum speed of the defending unmanned surface vessel.

[0028] The interception effectiveness evaluation indicators include interception result, interception time, average distance relative to the target point, mission point error distance, and interception impact factor. The interception result refers to whether the defended target point is destroyed. The interception time is the duration from when the defending UAV detects the attacking UAV to when the attacking UAV is destroyed or the attacking UAV destroys the target point. The average distance relative to the target point measures the additional movement of the attacking UAV relative to the target point caused by the interception behavior of the defending UAV. The mission point error distance measures the distance difference between the defending UAV and its required mission. The interception impact factor measures the interception influence of the defending UAV on the attacking UAV and depends on the relative positions of the defending UAV, the attacking UAV, and the target point.

[0029] The formula for calculating the error distance of the task point is as follows:

[0030]

[0031] Where N is the number of unmanned surface vessels (USVs) of the defending side, and X... i X represents the position of each defending unmanned surface vessel i in the cluster. s,i This refers to the mission point location corresponding to the defending unmanned surface vessel i.

[0032] The interception impact factor β L The formula for calculating ∈[0,1] is as follows:

[0033]

[0034] Where N is the number of unmanned surface vessels on the defending side, β L,i Let be the individual interception impact factor of the defending unmanned surface vessel i, defined as follows:

[0035]

[0036] Among them, R d,i This indicates the distance between the defending unmanned surface vessel i and the target point. L represents the angle between the i-th defender, the target point, and the attacker. i R represents the distance from the defending unmanned surface vessel i to the line connecting the attacking side and the target point. a This represents the distance between the attacking unmanned surface vessel and the target point.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] (1) Based on the completion of problem modeling, considering that the speed and maneuverability of the defending unmanned surface vessel (USV) are inferior to those of the attacking USV when intercepting USV swarms, this invention proposes a predictive interception method based on passive defense. The defending USV swarm does not take the initiative to attack, but chooses to passively defend and wait for the attacking USV to launch a surprise attack. The heuristic task allocation search algorithm assigns task targets to the USV swarm, and obtains corresponding task points without path intersections. This can make full use of our swarm advantage and position advantage to make up for the speed disadvantage, better execute the interception task, and improve the mission success rate of USV swarms in the variable marine environment.

[0039] (2) This invention designs an improved artificial potential field method for attacking unmanned surface vessels (USVs) to achieve path planning and dynamic obstacle avoidance, thereby avoiding interception and encirclement by defending USVs. Compared with the classic artificial potential field method, it is more flexible in the face of dynamic obstacles and can avoid getting trapped in local optima, enabling attacking USVs to effectively avoid interception by defending USVs in complex and ever-changing marine environments, thus improving the flexibility and adaptability of the mission.

[0040] (3) The heuristic task allocation search algorithm of the present invention takes into account the relative position of the unmanned surface vessel and the relative position of the task point, which can enable the unmanned surface vessel to better match task points with similar relative positions when allocating tasks, avoid the intersection between the paths of the unmanned surface vessel to the assigned task point, and thus avoid the possibility of collision due to path intersection to a certain extent.

[0041] (4) This invention has the characteristics of simple structure and high success rate. It can be applied to unmanned ship clusters of different sizes and complete autonomous and collaborative interception tasks.

[0042] (5) This invention designs multiple evaluation indicators for the interception effect of unmanned surface vessel swarms to evaluate the interception effect, which can improve the interception effect to a certain extent. Attached Figure Description

[0043] Figure 1 This is a flowchart of the method of the present invention.

[0044] Figure 2 This is a schematic diagram of the impact radius in one embodiment.

[0045] Figure 3 This is a schematic diagram of the defense radius in one embodiment.

[0046] Figure 4 This is a schematic diagram of a passive defense method in one embodiment.

[0047] Figure 5 This is a schematic diagram of the artificial potential field method in one embodiment.

[0048] The attached diagram is labeled as follows: 1. First offensive unmanned surface vessel (USV); 2. Second offensive USV; 3. First defensive USV; 4. Second defensive USV; 5. Third defensive USV; 6. Strike radius R h 7. Defending target; 8. Distance R of attacking unmanned surface vessel from defending target a 9. Defense radius R d 10. Angle between the defending unmanned surface vessel (USV), the defending target, and the attacking USV; 11. Distance from the defending USV to the line connecting the attacking USV and the target point; 12. Repulsive force of the first defending USV; 13. Repulsive force of the second defending USV; 14. Attractiveness of the defending target. Detailed Implementation

[0049] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0050] This embodiment provides a passive defense-based method for intercepting unmanned surface vessel (USV) swarms, such as... Figure 1 As shown, it includes the following steps:

[0051] S1, based on the speed and maneuverability differences between the defender and the attacker, establishes motion models for the unmanned surface vessels of the defender and the attacker.

[0052] The motion models of the defending and attacking unmanned surface vessels are as follows: For unmanned surface vessel i, its position at time t is (x i (t),y i (t)), where longitudinal velocity and heading are respectively expressed as v. i (t) and θ i (t), then according to the principles of kinematics, calculate the position of the unmanned surface vessel at the next moment t+Δt:

[0053] x i (t+Δt)=x i (t)+v i (t)cos(θ i (t))

[0054] y i (t+Δt)=y i (t)+y i (t)sin(θ i (t))

[0055] S2 defines the strike radius and defense radius. Objects approaching the strike radius of the unmanned surface vessel (USV) will be destroyed. The defense radius is the distance between the defending USV and the target point. The passive defense method is used to predict the path of the attacking USV, and a heuristic task allocation search algorithm is used to allocate task targets to the defending USV cluster.

[0056] Introducing the strike radius R h The concept is close to the radius R of the unmanned surface vessel. h The objects inside will be destroyed. For example... Figure 2 As shown, when the defending unmanned surface vessel directly intercepts the attacking unmanned surface vessel, that is, when the attacking unmanned surface vessel approaches the target point R... h The unmanned surface vessel R that had previously approached the attacking side within range h Within the target area, if the attacking unmanned surface vessel (USV) is destroyed, the objective point is protected, the defending side wins, and the interception is successful. Conversely, if the attacking USV avoids the defending USV, that is, when the defending USV approaches its own R... h The target point R was previously within the range. h Within the target area, if the target point is destroyed, the attacking side wins and the interception fails.

[0057] like Figure 3 As shown, a defensive radius R is introduced. d The distance between the defending unmanned surface vessel (USV) and the target point reflects, to some extent, the interception influence of the USV's area. During the pursuit between the attacker and defender, the attacker, to bypass the defender and approach the target point, needs to utilize its speed advantage to move in an arc-shaped trajectory. Because the defender is slower, when the radius of the arc is the same, the distance traveled in the same amount of time is much less than the attacker's. At this point, there is no longer a defender blocking the path between the attacker and the target point, allowing the attacker to easily break through the defender's interception. When at a speed disadvantage, the defending USV does not adopt an offensive strategy but chooses passive defense, waiting for a surprise attack from the attacker's USV to maintain its interception influence, which can improve the effectiveness of the interception to some extent.

[0058] Based on the above ideas, it can be predicted that the general direction of the attacking unmanned surface vessel's (USV) movement will inevitably be towards the target point. The defending USV swarm will no longer send individual members to track the attacking USV; instead, based on speed differences, they will form a defensive ring within a certain defensive radius, awaiting the opponent's attack. Figure 4 As shown.

[0059] For the attacking unmanned surface vessel, the distance to the target point is R. a The speed is v a For the defending unmanned surface vessel, the defense radius is R. d The speed is v d And v d <v a During the engagement between the attacking and defending unmanned surface vessels (USVs), their trajectories are considered as concentric circles centered on the target point, with radii R and R, respectively. a and R dTo ensure that there is always a defending unmanned surface vessel on the line connecting the attacker and the target point, the following should be true:

[0060]

[0061] Based on the determined defense radius, task target points are selected evenly on the concentric circles, and task points are assigned to the unmanned surface vessel cluster using a heuristic task allocation search algorithm to execute the encirclement and interception task.

[0062] For a swarm of N unmanned surface vessels (USVs), N tasks need to be identified to intercept and capture the target. Specifically, the defender uses a heuristic task allocation search algorithm based on known information to assign N target points derived from the predictive interception method to each of the N USVs.

[0063] The defending unmanned surface vessel cluster is denoted as set. The task objectives are denoted as set. The mission objective of unmanned surface vessel i is denoted as q. i The task allocation for the entire unmanned surface vessel swarm is denoted as Q = q1,...,q N For each unmanned surface vessel i, calculate the distance dis(i,s) between it and each mission objective:

[0064]

[0065] Prioritize targets that are closer, i.e., the task objective that satisfies the requirement of the shortest distance:

[0066]

[0067] To further improve the efficiency of heuristic search, the relative positions of the unmanned surface vessels (USVs) and the task points are taken into account. To simplify calculations, this embodiment uses the USV swarm center as a reference, with the distance between each USV and the swarm center serving as the measure of its relative position. Similarly, using the task target point center as a reference, the distance between each task target point and its center serves as the measure of its relative position. After reordering the USVs by their relative positions from closest to farthest, a heuristic search is then performed. The updated search formula is as follows:

[0068]

[0069] Where f1(i) represents the distance sorted of the unmanned surface vessel numbered i from the center of the unmanned surface vessel cluster, and f2(s) represents the distance sorted of the mission target point numbered s from the center of the mission target point among all mission targets.

[0070] Reordering the unmanned surface vessel (USV) and task points based on their center distance allows for better matching of relatively similar task points during task allocation, improving the search efficiency of the USV during task execution. Furthermore, during task allocation, intersections between paths leading to assigned task points should be avoided as much as possible to mitigate the possibility of collisions due to intersecting paths.

[0071] In S3, the attacking unmanned surface vessel (USV) uses an improved artificial potential field method for path planning and dynamic obstacle avoidance to evade the interception of the defending USV.

[0072] The core idea of ​​the classic artificial potential field method is to construct an gravitational potential field centered on the target point to attract the robot and to construct a repulsive potential field centered on the obstacle to repel the robot and drive it away. The unmanned surface vessel's movement is guided by the combined force field of the gravitational and repulsive fields. Figure 5 As shown.

[0073] However, when planning trajectories around dynamic obstacles, it is necessary to determine the obstacle's position in the next moment by knowing its current position and motion, thereby avoiding collisions. Based on this idea, this embodiment improves the repulsive field of the artificial potential field method. The repulsive potential energy intensity is related not only to the distance between the unmanned surface vessel and the obstacle but also to the obstacle's velocity. The repulsive potential field is improved as follows:

[0074]

[0075] Among them, X i X j k represents the position of the unmanned surface vessel and the position of the obstacle, respectively. req ρ(X) is the repulsive gain coefficient. j ,X i Let ρ be the vector pointing from the location of the obstacle to the location of the unmanned surface vessel. o Let be a constant, representing the maximum distance at which the obstacle exerts a repulsive force on the unmanned surface vessel (USV), p be the direction vector from the defending USV to the attacking USV, and v be a constant. a,max This represents the maximum speed of the defending unmanned surface vessel.

[0076] In the special case where the repulsive force of obstacles and the gravitational force of the target point are on the same straight line, the unmanned surface vessel (USV) may get stuck in a local optimum and fail to reach the target point because the repulsive force is greater than or equal to the gravitational force. The improved approach is to introduce a hypothetical small perturbation repulsive force to break the equilibrium point and allow the USV to escape the local optimum, thus avoiding the situation where the resultant repulsive force and gravitational force are collinear.

[0077] S4 evaluates the interception effect of the unmanned surface vessel swarm based on multiple interception effect evaluation indicators.

[0078] The evaluation indicators for interception effectiveness include interception results, interception time, average distance relative to the target point, error distance at the mission point, and interception impact factor.

[0079] (1) Interception result G: Whether the defended target point has been destroyed.

[0080] (2) Interception time t l : The time elapsed from when the defending unmanned surface vessel (USV) detects the attacking USV until it is destroyed or the attacking USV destroys the target point; if the interception is successful, the interception time t. l The shorter the time, the better the interception effect; in the case of interception failure, the interception time t l The longer the interval, the more time the defending unmanned surface vessel gains during the interception process, indicating a better interception effect.

[0081] (3) Average distance relative to the target point Measure the additional relative movement of the attacking unmanned surface vessel (USV) to the target point caused by the interception action of the defending USV.

[0082] (4) Task point error distance d e Used to measure the distance difference between the defending unmanned surface vessel and the target vessel's required mission; d e The distance between the location of each defending unmanned surface vessel in the cluster and its corresponding mission point is calculated, and then the average of these distances is obtained. The calculation formula is as follows:

[0083]

[0084] Where N is the number of unmanned surface vessels (USVs) of the defending side, and X... i X represents the position of each defending unmanned surface vessel i in the cluster. s,i This refers to the mission point location corresponding to the defending unmanned surface vessel i.

[0085] (5) The interception impact factor is used to measure the interception influence of the defending unmanned surface vessel on the attacking side. It depends on the relative positions between the defending unmanned surface vessel, the attacking unmanned surface vessel and the target point.

[0086] Interception Impact Factor β L The formula for calculating ∈[0,1] is as follows:

[0087]

[0088] Where N is the number of unmanned surface vessels on the defending side, β L,i Let be the individual interception impact factor of the defending unmanned surface vessel i, defined as follows:

[0089]

[0090] Among them, R d,i This indicates the distance between the defending unmanned surface vessel i and the target point. L represents the angle between the i-th defender, the target point, and the attacker. i R represents the distance from the defending unmanned surface vessel i to the line connecting the attacking side and the target point. a This represents the distance between the attacking unmanned surface vessel and the target point.

[0091] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for intercepting unmanned surface vessel swarms based on passive defense, characterized in that, Includes the following steps: S1. Based on the speed and maneuverability differences between the defender and the attacker, establish motion models for the unmanned surface vessels of the defender and the attacker. S2 defines the strike radius and defense radius. Objects approaching the strike radius of the unmanned surface vessel will be destroyed. The defense radius is the distance between the defending unmanned surface vessel and the target point. The passive defense method is used to predict the path of the attacking unmanned surface vessel, and a heuristic task allocation search algorithm is used to allocate task targets to the defending unmanned surface vessel cluster. S3, the attacking unmanned surface vessel uses an improved artificial potential field method for path planning and dynamic obstacle avoidance to avoid the interception of the defending unmanned surface vessel; S4. Evaluate the interception effect of the unmanned surface vessel swarm based on multiple interception effect evaluation indicators. For a scale of N The defender, based on known information, employs a heuristic task allocation search algorithm to address the unmanned surface vessel swarm. N The method of assigning unmanned surface vessels to predictive interception was derived. N The heuristic task allocation search algorithm is as follows: There are several task target points. The defending unmanned surface vessel cluster is denoted as set. The task objectives are denoted as set. Unmanned surface vessel The task objective is denoted as The task allocation for the entire unmanned surface vessel swarm is denoted as For each unmanned surface vessel Calculate the distance between each target and each mission objective. : Using the center of the unmanned surface vessel (USV) swarm as a reference, the distance between each individual in the swarm and the swarm center is used as the standard for measuring the relative position of the individual. Using the center of the mission objective point as a reference, the distance between each mission objective point and the mission objective point center is used as the standard for measuring the relative position of the mission objective point. After reordering the individuals and mission objective points from nearest to farthest, a heuristic search is then used. The search formula is as follows: in, Indicates number The unmanned surface vessels (USVs) are sorted by their distance from the cluster center within the USV swarm. Indicates number The task objective points are sorted by their distance from the center of the task objective points among all task objectives.

2. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 1, characterized in that, The motion models for the defending and attacking unmanned surface vessels are as follows: For the unmanned surface vessel... At any moment The location is The longitudinal speed and heading are respectively expressed as and Then, based on the principles of kinematics, the next moment is calculated. Location of the unmanned surface vessel: 。 3. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 1, characterized in that, When the defender's speed and maneuverability are lower than the attacker's, the defender's unmanned surface vessels (USVs) do not take the initiative to attack, but instead choose to defend passively. Based on the general direction of the attacker's USV movement, which will inevitably be towards the target point, the defender's USV swarm forms a defensive ring within the defensive radius, waiting for the opponent's attack.

4. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 3, characterized in that, Step S2 specifically involves: for the attacking unmanned surface vessel, the distance to the target point is... The speed is ; For the defending unmanned surface vessel, the defense radius is... The speed is ,and During the engagement between the attacking and defending unmanned surface vessels (USVs), their trajectories are considered as concentric circles centered on the target point, with radii of... and To ensure that there is always a defending unmanned surface vessel on the line connecting the attacker and the target point, the following should be true: Based on the determined defense radius, task target points are selected evenly on the concentric circles, and task points are assigned to the unmanned surface vessel cluster using a heuristic task allocation search algorithm to execute the encirclement and interception task.

5. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 1, characterized in that, The improved artificial potential field method specifically involves setting an artificial potential field function to guide the movement of the unmanned surface vessel. The artificial potential field function includes an attractive potential field and a repulsive potential field. The repulsive potential field is improved for dynamic obstacles. At the same time, in order to avoid the situation where the net repulsive force and the attractive force are collinear, a fictitious small perturbation repulsive force is introduced to break the equilibrium point.

6. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 5, characterized in that, The improved repulsive potential field for dynamic obstacles specifically refers to: Based on the relationship between the repulsive potential energy intensity and the distance between the unmanned surface vessel and the obstacle, as well as the speed of the obstacle, the repulsive potential field is improved as follows: in, , These represent the positions of the unmanned surface vessel and the obstacles, respectively. The repulsive gain coefficient is... Let be the vector pointing from the location of the obstacle to the location of the unmanned surface vessel. The constant represents the maximum distance at which an obstacle exerts a repulsive force on the unmanned surface vessel. The direction vector from the defending unmanned surface vessel (USV) to the attacking USV. This represents the maximum speed of the defending unmanned surface vessel.

7. The method for intercepting unmanned surface vessel swarms based on passive defense according to claim 1, characterized in that, The interception effectiveness evaluation indicators include interception result, interception time, average distance relative to the target point, mission point error distance, and interception impact factor. The interception result refers to whether the defended target point is destroyed. The interception time is the duration from when the defending UAV detects the attacking UAV to when the attacking UAV is destroyed or the attacking UAV destroys the target point. The average distance relative to the target point measures the additional movement of the attacking UAV relative to the target point caused by the interception behavior of the defending UAV. The mission point error distance measures the distance difference between the defending UAV and its required mission. The interception impact factor measures the interception influence of the defending UAV on the attacking UAV and depends on the relative positions of the defending UAV, the attacking UAV, and the target point.

8. A method for intercepting unmanned surface vessel swarms based on passive defense according to claim 7, characterized in that, The formula for calculating the error distance of the task point is as follows: in, N The number of unmanned surface vessels of the defending side. For each defending party's unmanned surface vessel in the cluster Its own position, For the defending unmanned surface vessel The corresponding task location.

9. A method for intercepting unmanned surface vessel swarms based on passive defense according to claim 7, characterized in that, The interception impact factor The calculation formula is as follows: in, N The number of unmanned surface vessels of the defending side. For the defending unmanned surface vessel The individual interception impact factor is defined as follows: in, Indicates the defending unmanned surface vessel Distance from the target point Indicates the first The angle between the defender, the target point, and the attacker. Indicates the defending unmanned surface vessel The distance to the line connecting the attacking side and the target point. This represents the distance between the attacking unmanned surface vessel and the target point.

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