A local area oriented UAV swarm attack method

Abstract

The present application belongs to the field of unmanned aerial vehicle group confrontation, and discloses a kind of local area-oriented unmanned aerial vehicle group attack method, mainly solve unmanned aerial vehicle group attack problem, main implementation steps are: based on electromagnetic spectrum positioning method obtains the positioning of opposite unmanned aerial vehicle group in task area;Based on unmanned aerial vehicle group positioning analysis opposite unmanned aerial vehicle group topological relationship;Based on the topological relationship of opposite unmanned aerial vehicle group, analyze its key node;Strike key node, go to step (1), continue to execute until opposite key node is struck completely.This application gives a kind of local area unmanned aerial vehicle group positioning method to obtain unmanned aerial vehicle group topological relationship, the topological relationship of unmanned aerial vehicle group is analyzed by the way of multistage clustering and unit circle confirmation, and the key node of unmanned aerial vehicle group is judged according to unmanned aerial vehicle group topological relationship and signal strength, finally based on multi-wheel unmanned aerial vehicle group attack mechanism, until all key nodes are knocked down.

Description

Technical Field

[0001] This invention belongs to the field of drone swarm countermeasures, and particularly relates to a method for attacking drone swarms in localized areas. Background Technology

[0002] Unmanned aerial vehicle (UAV) swarm technology refers to an intelligent technology that uses modern control and decision-making methods to maintain multiple unmanned aerial vehicles (UAVs) with common mission objectives in an orderly manner to perform tasks. UAV swarm technology can make intelligent decisions with minimal human intervention and has advantages such as self-organization, collaboration, parallelism, and security, making it an inevitable trend in the future informatization and intelligentization of aircraft technology. With the rapid development of control, communication, sensor, and intelligent scheduling technologies, UAV swarm technology has been widely applied in civilian and military fields such as regional telemetry and search, military reconnaissance and strike, information communication, meteorological monitoring, and logistics transportation. It has gradually replaced manned systems, especially in remote, dangerous, or inaccessible working environments.

[0003] Unmanned aerial vehicle (UAV) swarms are closely coupled entities within a mission area. Their mission execution relies on the capabilities of each UAV and aims to maximize benefits, requiring the rational allocation of tasks and limited resources. With the widespread application of UAV swarms, their defense and countermeasures have become a hot topic. Therefore, effectively detecting UAV swarms and developing appropriate countermeasure strategies is of paramount importance. Summary of the Invention

[0004] The number of drone swarms in the mission area is uncertain, but the mission area can be divided into multiple local areas. The number of drone swarms in a particular local area of ​​the mission area is limited, thus limiting the hierarchical divisions and the topological relationships within that local area are not overly complex. Therefore, the key technical problem this invention aims to solve is to propose a method for attacking drone swarms in local areas. This invention addresses the above problem by proposing a method for attacking drone swarms in local areas to solve the problem of drone swarm attacks.

[0005] To achieve the above objectives, the technical solution of the present invention includes the following steps:

[0006] A method for targeting drone swarms in a localized area includes the following steps:

[0007] (1) Obtain the location of the enemy's UAV swarm within the mission area based on the electromagnetic spectrum positioning method;

[0008] (2) Analyze the topological relationship of the other drone swarm based on drone swarm positioning;

[0009] (3) Analyze key nodes based on the topology of the other party's drone swarm;

[0010] (4) Strike the key nodes, then go to step (1) and continue until the opponent's key nodes have been attacked.

[0011] Furthermore, the specific process of step (1) is as follows:

[0012] (1a) Deploy at least three spectrum acquisition points at the edge of the operational area;

[0013] (1b) The spectrum acquisition point collects the spectrum information and sends it to the ground monitoring terminal;

[0014] (1c) The ground monitoring terminal uses time difference positioning method based on spectrum information to locate all units with electromagnetic signals in the combat area;

[0015] (1d) Based on the positioning results, aerial targets are selected. The specific selection method is: targets with elevation information greater than a set threshold are aerial targets, thereby obtaining the positioning information of the other party's drone swarm.

[0016] Furthermore, the specific analysis process of step (2) is as follows:

[0017]

[0018] In the formula, UAV represents the opposing drone swarm, Fc(UAV) represents the first-level clustering of the opposing drone swarm, N is the number of cluster centers, and Fc(UAV) j Let Fc(Fc(UAV)) represent the j-th first-level cluster center, Fc(Fc(UAV)) represent the second-level clustering of the opposing UAV swarm, Num(Fc(UAV)) represent the number of first-level cluster centers of the opposing UAV swarm, and Cir() represent whether there is a UAV node within the unit circle centered on the cluster center (1 if present, 0 if absent). The six topological relationships are as follows:

[0019] Case 1: Two-layer distributed architecture, namely "distributed + single machine";

[0020] Case 2: Two-tier centralized architecture, namely "centralized + standalone";

[0021] Case 3: Three-tier distributed architecture, namely "distributed + distributed + single machine";

[0022] Case 4: Three-tier hybrid architecture, namely "distributed + centralized + stand-alone";

[0023] Case 5: Three-tier hybrid architecture, namely "centralized + distributed + stand-alone";

[0024] Case 6: Three-tier centralized architecture, namely "centralized + centralized + standalone".

[0025] Furthermore, the specific process of step (3) is as follows:

[0026] For hybrid and centralized architectures, the central drone node is the key node;

[0027] For a distributed architecture, the average signal strength of each node of the drone is calculated within a set time period. Nodes with an average signal strength higher than a threshold are considered critical nodes.

[0028] Compared with the prior art, the present invention has the following advantages:

[0029] 1. This invention provides a method for locating unmanned aerial vehicle (UAV) swarms within a local area. Based on electromagnetic spectrum information, a time difference positioning method is used to obtain all electromagnetic targets within the local area. Then, aerial targets are selected based on the positioning results. Specifically, targets with elevation information greater than a certain threshold are considered aerial targets. This allows the acquisition of the positioning information of the UAV swarm. The method is simple, effective, and robust.

[0030] 2. This invention provides a method for analyzing the topological relationships of a local UAV swarm. Specifically, through multi-level clustering and unit circle confirmation, the topological relationships of the UAV swarm are divided into six types: two-layer distributed, two-layer centralized, three-layer distributed, three-layer hybrid (distributed + centralized + single UAV), three-layer hybrid (centralized + distributed + single UAV), and three-layer centralized. The analysis method is simple, effective, and robust, and the topological relationship classification comprehensively covers various types.

[0031] 3. This invention provides a method for judging key nodes in a drone swarm, which is based on the topological relationship and signal strength of the drone swarm. The judgment method is simple, effective and robust.

[0032] 4. This invention provides a multi-round drone swarm attack mechanism until all key nodes are destroyed, and the attack method is direct and effective. Attached Figure Description

[0033] Figure 1 This is the overall flowchart of the present invention.

[0034] Figure 2 This is a two-layer distributed (distributed + single-machine) topology diagram of a drone swarm.

[0035] Figure 3 This is a topology diagram of a two-layer centralized (centralized + single-unit) drone swarm.

[0036] Figure 4 This is a three-layer distributed (distributed + distributed + single-machine) topology diagram of a drone swarm.

[0037] Figure 5This is a three-layer hybrid (distributed + centralized + single-unit) topology diagram of a drone swarm.

[0038] Figure 6 This is a three-layer hybrid (centralized + distributed + single-unit) topology diagram of a drone swarm.

[0039] Figure 7 This is a three-layer centralized (centralized + centralized + single-unit) topology diagram of a drone swarm. Detailed Implementation

[0040] The following will clearly and completely describe the concept, technical advantages, and resulting technical effects of the present invention with reference to embodiments, so as to fully understand the purpose, features, and effects of the present invention. It should be noted that the specific embodiments described herein are only used to explain the present invention and do not limit the present invention.

[0041] See Figure 1 A method for striking drone swarms in a localized area includes the following steps:

[0042] (1) The location of the enemy UAV swarm within the mission area is obtained based on the electromagnetic spectrum positioning method, specifically as follows:

[0043] (1a) Deploy at least three spectrum acquisition points at the edge of the operational area (four were deployed in this embodiment);

[0044] (1b) The spectrum acquisition point collects the spectrum information and sends it to the ground monitoring terminal;

[0045] (1c) The ground monitoring terminal uses time difference positioning method based on spectrum information to locate all units with electromagnetic signals in the combat area;

[0046] (1d) Based on the positioning results, aerial targets are selected. The specific selection method is: targets with elevation information greater than a set threshold are aerial targets, thereby obtaining the positioning information of the other party's drone swarm.

[0047] (2) Based on the analysis of the topological relationship of the other drone swarm, the specific method is as follows:

[0048]

[0049] In the formula, UAV represents the opposing drone swarm, with M drones, and Fc(UAV) represents the first-level clustering of the opposing drone swarm, with n cluster centers. jLet Fc(Fc(UAV)) represent the j-th first-level cluster center, Fc(Fc(UAV)) represent the second-level clustering of the opposing UAV swarm, Num(Fc(UAV)) represent the number of first-level cluster centers of the opposing UAV swarm, and Cir() represent whether there are any UAV nodes within the unit circle centered on the cluster center (1 for existence, 0 for non-existence). Analysis reveals six possible topological relationships, as follows:

[0050] ①Case 1: Two-tier distributed architecture, i.e., "distributed + single-machine", such as Figure 2 As shown;

[0051] ②Case 2: Two-tier centralized architecture, i.e., "centralized + standalone", such as Figure 3 As shown;

[0052] ③Case 3: Three-tier distributed architecture, namely "distributed + distributed + standalone", such as Figure 4 As shown;

[0053] ④Case 4: Three-tier hybrid architecture, namely "distributed + centralized + standalone", such as Figure 5 As shown;

[0054] ⑤ Case 5: Three-tier hybrid architecture, namely "centralized + distributed + standalone", such as Figure 6 As shown;

[0055] ⑥Case 6: Three-tier centralized architecture, i.e., "centralized + centralized + standalone", such as Figure 7 As shown.

[0056] (3) Based on the topology of the opposing drone swarm, analyze its key nodes. The specific method is as follows:

[0057] For hybrid and centralized architectures, the central drone node is the key node;

[0058] For a distributed architecture, the average signal strength of each node of the drone is statistically analyzed over a period of time. Nodes with higher average signal strength (above a set threshold) are considered key nodes, because a high average signal strength means a large amount of information is transmitted. Although it is a distributed architecture, drone nodes that transmit a large amount of information are often located in hotspot areas or have a high tactical position.

[0059] (4) After completing one round of attacks on the enemy's drone swarm, proceed to step (1) and continue until the enemy's key nodes have been attacked.

Claims

1. A method for striking unmanned aerial vehicle (UAV) swarms in a localized area, characterized in that: Includes the following steps: (1) Obtain the location of the enemy UAV swarm within the mission area based on the electromagnetic spectrum positioning method; (2) Analyze the topological relationship of the other drone swarm based on drone swarm positioning; (3) Analyze key nodes based on the topology of the other party's drone swarm; (4) Strike the key nodes, then go to step (1) and continue until the opponent's key nodes have been attacked. The specific analysis process of step (2) is as follows: In the formula, Indicates the other party's drone swarm. This indicates that the other party's drone swarm is clustered at level 1. The number of cluster centers. Indicates the first One first-level cluster center, This indicates that the other party's drone swarm is being clustered at level 2. This indicates the number of Level 1 cluster centers of the opposing drone swarm. This indicates whether there are any unmanned aerial vehicle (UAV) nodes within the unit circle centered on the cluster center; if so, then... The value is 1, or it does not exist. A value of 0; 6 topological relationships, as follows: Case 1: Two-tier distributed architecture, namely "distributed + single machine"; Case 2: Two-tier centralized architecture, namely "centralized + standalone"; Case 3: Three-tier distributed architecture, namely "distributed + distributed + stand-alone"; Case 4: Three-tier hybrid architecture, namely "distributed + centralized + standalone"; Case 5: Three-tier hybrid architecture, namely "centralized + distributed + stand-alone"; Case 6: Three-tier centralized architecture, namely "centralized + centralized + standalone"; The specific process of step (3) is as follows: For hybrid and centralized architectures, the central drone node is the key node; For a distributed architecture, the average signal strength of each node of the drone is calculated within a set time period. Nodes with an average signal strength higher than a threshold are considered critical nodes.

2. The method for attacking unmanned aerial vehicle swarms targeting a local area according to claim 1, characterized in that, The specific process of step (1) is as follows: (1a) Deploy at least three spectrum acquisition points at the edge of the operational area; (1b) The spectrum acquisition point will collect the spectrum information and send it to the ground monitoring terminal; (1c) The ground monitoring terminal uses time difference positioning method based on spectrum information to locate all units with electromagnetic signals in the combat area; (1d) Based on the positioning results, aerial targets are selected. The specific selection method is: targets with elevation information greater than a set threshold are aerial targets, thereby obtaining the positioning information of the other party's UAV swarm.

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