Methods, systems, equipment and storage media for threat assessment of drone swarm targets
By conducting threat assessments of the area surrounding drone swarm targets and calculating combat power and distance threat indices, a scientific basis is provided for the defense strategies of naval fleets. This solves the problem of threat assessment of drone swarms to radar stations and improves the effectiveness of defense.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA SHIP DEV & DESIGN CENT
- Filing Date
- 2023-05-19
- Publication Date
- 2026-05-26
Smart Images
Figure CN116629674B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) swarm technology, specifically relating to a method, system, device, and storage medium for assessing the target threat of UAV swarms. Background Technology
[0002] With the rapid development of cutting-edge technologies such as drones, artificial intelligence, communication networks, and big data, a new combat mode has emerged and gained popularity: drone swarm warfare. Due to the poor maneuverability and high value of large surface ships, they will become ideal targets for drone swarms. In future maritime operations, saturation attacks by drone swarms will become an asymmetric warfare tactic. Threat assessment is a crucial element in counter-drone swarm operations by naval formations. Summary of the Invention
[0003] The purpose of this invention is to provide a method, system, device, and storage medium for assessing the threat posed by drone swarms to targets, thereby solving the problem of threat assessment by drone swarms.
[0004] The technical solution adopted in this invention is as follows:
[0005] A method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets, comprising:
[0006] Divide the area surrounding the target into multiple zones;
[0007] Let n be the number of drones in region i of the drone swarm. i If the lethality of a drone against a target is ξ, then within region i, the combat threat index of a drone against a target is defined as Q. i The calculation formula is as follows:
[0008]
[0009] In the formula, k1 and k2 are parameters, and k1 ≤ 1;
[0010] Let d be the distance between the j-th UAV and the target in region i. ij The maximum kill radius of the j-th drone is d. jmax In region i, the distance threat index of the j-th UAV to the target is defined as D. i The calculation formula is as follows:
[0011]
[0012] From equations (1) and (2), we know that Q i Regarding n i Monotonically increasing, D i Regarding d ij Monotonically decreasing;
[0013] Combining equations (1) and (2), the threat index f of region i is obtained. i for:
[0014]
[0015] Right now:
[0016]
[0017] This allows us to derive the threat index for each area surrounding the target.
[0018] Furthermore, based on the attack direction or possible attack direction of the drone swarm towards the target, the area surrounding the target is divided into multiple zones.
[0019] A threat assessment system for drone swarm targets includes:
[0020] The region division module is used to divide the area surrounding the target into multiple regions;
[0021] The threat index module is used to define the number of drones in region i as n. i If the lethality of a drone against a target is ξ, then within region i, the combat threat index of a drone against a target is defined as Q. i The calculation formula is as follows:
[0022]
[0023] In the formula, k1 and k2 are parameters, and k1 ≤ 1;
[0024] Let d be the distance between the j-th UAV and the target in region i. ij The maximum kill radius of the j-th drone is d. jmax In region i, the distance threat index of the j-th UAV to the target is defined as D. i The calculation formula is as follows:
[0025]
[0026] From equations (1) and (2), we know that Q i Regarding n i Monotonically increasing, D i Regarding d ij Monotonically decreasing;
[0027] Combining equations (1) and (2), the threat index f of region i is obtained. i for:
[0028]
[0029] Right now:
[0030]
[0031] This allows us to derive the threat index for each area surrounding the target.
[0032] Furthermore, the area division module is used to divide the area surrounding the target into multiple areas based on the attack direction or possible attack direction of the drone swarm.
[0033] An electronic device, comprising:
[0034] Memory, used to store executable computer programs;
[0035] The processor, when executing an executable computer program stored in memory, implements the aforementioned method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets.
[0036] A computer-readable storage medium storing a computer program for implementing the above-described method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets when executed by a processor.
[0037] Compared with the prior art, the present invention has the following advantages and beneficial effects:
[0038] This invention divides the area surrounding the target into multiple regions, then performs a threat assessment on each region to obtain a threat index for each region, which serves as the basis for the threat assessment; and the threat indices can be ranked to provide a reference for the subsequent formulation of counter-drone swarm combat strategies. Attached Figure Description
[0039] Figure 1 This is a schematic diagram of an anti-drone swarm combat scenario according to an embodiment of the present invention;
[0040] Figure 2 This is a zoning map of the area surrounding the radar station according to an embodiment of the present invention. Detailed Implementation
[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be 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 illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.
[0042] This invention addresses the problem of threat assessment for drone swarm targets by constructing a threat assessment model based on threat assessment indicators, which calculates the threat index of the drone swarm as the basis for threat assessment.
[0043] In maritime counter-drone swarm operations, threat assessment indicators should be selected based on target data detected and collected by various sensors within the formation, and each indicator should have a direct or indirect relationship with the threat index. In common scenarios, drone swarm-related data is acquired through radar, which, due to its obvious and valuable target, has a high priority among drone swarm attack targets. In constructing the threat index for radar, the enemy's strength (i.e., the number of drones) and the distance between the drones and the radar are important factors. This invention first divides the area where the radar may be attacked, then performs a threat assessment on each area, derives a threat index, and ranks them, providing a reference for formulating counter-drone swarm combat strategies.
[0044] Figure 1 The text describes a maritime anti-drone swarm combat scenario. Below, suicide drones dominate, primarily targeting mobile radar stations. Above, a defensive posture is employed, featuring reconnaissance and strike drones, large unmanned surface vessels (USVs), and anti-aircraft artillery positions, with the main mission of protecting the radar stations from destruction.
[0045] according to Figure 1 In a medium-scale combat scenario, the drones above, acting as the defenders, need to rationally allocate their combat and firepower units when the drone swarm below launches an attack. The first step is to conduct a threat assessment. Centered on the radar station, the possible attack directions of the drone swarm below are divided into four zones, such as... Figure 2 As shown. Figure 2 It describes the regional division centered on the radar station.
[0046] The threat level of the drone swarm to the radar station is mainly related to two parameters: the size of the troop strength and the distance between the drones and the mobile radar station. Generally speaking, the larger the troop strength, the greater the threat level to the radar station; the smaller the distance between the drones and the mobile radar station, the greater the threat level.
[0047] Let n be the number of drones in region i of the drone swarm. i If the lethality of a drone to a radar station is ξ, then within region i, the combat threat index of a drone to a radar station is defined as Q. i The calculation formula is as follows:
[0048]
[0049] In the formula, k1 and k2 are parameters, and k1 ≤ 1.
[0050] Let d be the distance between the j-th UAV and the radar station in region i. ij The maximum kill radius of the j-th drone is d. jmaxIn region i, the distance threat index of the j-th UAV to the radar station is defined as D. i The calculation formula is as follows:
[0051]
[0052] From equations (1) and (2), we can see that Q i Regarding n i Monotonically increasing, D i Regarding d ij The threat index decreases monotonically, consistent with the previous analysis. Therefore, combining equations (1) and (2), the threat index of region i can be obtained. The threat index of region i is defined as f. i .
[0053]
[0054] Combining equations (1), (2), and (3), we can derive:
[0055]
[0056] Therefore, the threat index for each region can be obtained.
[0057] Ranking the threat index can provide a reference for formulating counter-drone swarm warfare strategies. Areas with high threat indices require enhanced defense capabilities.
[0058] A threat assessment system for drone swarm targets includes:
[0059] The region division module is used to divide the area surrounding the target into multiple regions;
[0060] The threat index module is used to define the number of drones in region i as n. i If the lethality of a drone against a target is ξ, then within region i, the combat threat index of a drone against a target is defined as Q. i The calculation formula is as follows:
[0061]
[0062] In the formula, k1 and k2 are parameters, and k1 ≤ 1;
[0063] Let d be the distance between the j-th UAV and the target in region i. ij The maximum kill radius of the j-th drone is d. jmax In region i, the distance threat index of the j-th UAV to the target is defined as D. i The calculation formula is as follows:
[0064]
[0065] From equations (1) and (2), we know that Q i Regarding n i Monotonically increasing, D i Regarding d ij Monotonically decreasing;
[0066] Combining equations (1) and (2), the threat index f of region i is obtained. i for:
[0067]
[0068] Right now:
[0069]
[0070] This allows us to derive the threat index for each area surrounding the target.
[0071] Furthermore, the area division module is used to divide the area surrounding the target into multiple areas based on the attack direction or possible attack direction of the drone swarm.
[0072] An electronic device, comprising:
[0073] Memory, used to store executable computer programs;
[0074] The processor, when executing an executable computer program stored in memory, implements the aforementioned method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets.
[0075] A computer-readable storage medium storing a computer program for implementing the above-described method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets when executed by a processor.
[0076] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.
[0077] Those skilled in the art will readily understand that the above are merely preferred embodiments of the present invention and are 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 within the scope of protection of the present invention.
Claims
1. A method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets, characterized in that, include: Divide the area surrounding the target into multiple zones; Let n be the number of drones in region i of the drone swarm. i If the lethality of a drone against a target is ξ, then within region i, the combat threat index of a drone against a target is defined as Q. i The calculation formula is as follows: In the formula, k1 and k2 are parameters, and k1 ≤ 1; Let d be the distance between the j-th UAV and the target in region i. ij The maximum kill radius of the j-th drone is d. jmax In region i, the distance threat index of the j-th UAV to the target is defined as D. i The calculation formula is as follows: From equations (1) and (2), we know that Q i Regarding n i Monotonically increasing, D i Regarding d ij Monotonically decreasing; Combining equations (1) and (2), the threat index f of region i is obtained. i for: Right now: This allows us to derive the threat index for each area surrounding the target.
2. The method for assessing the threat of unmanned aerial vehicle (UAV) swarm targets according to claim 1, characterized in that, Based on the direction of attack or possible direction of attack of the drone swarm on the target, the area surrounding the target is divided into multiple zones.
3. A threat assessment system for unmanned aerial vehicle (UAV) swarm targets, characterized in that, include: The region division module is used to divide the area surrounding the target into multiple regions; The threat index module is used to define the number of drones in region i as n. i If the lethality of a drone against a target is ξ, then within region i, the combat threat index of a drone against a target is defined as Q. i The calculation formula is as follows: In the formula, k1 and k2 are parameters, and k1 ≤ 1; Let d be the distance between the j-th UAV and the target in region i. ij The maximum kill radius of the j-th drone is d. jmax In region i, the distance threat index of the j-th UAV to the target is defined as D. i The calculation formula is as follows: From equations (1) and (2), we know that Q i Regarding n i Monotonically increasing, D i Regarding d ij Monotonically decreasing; Combining equations (1) and (2), the threat index f of region i is obtained. i for: Right now: This allows us to derive the threat index for each area surrounding the target.
4. The UAV swarm target threat assessment system according to claim 3, characterized in that, The area division module is used to divide the area around the target into multiple areas based on the attack direction or possible attack direction of the drone swarm.
5. An electronic device, characterized in that, include: Memory, used to store executable computer programs; The processor, when executing an executable computer program stored in memory, implements the drone swarm target threat assessment method as described in claim 1 or 2.
6. A computer-readable storage medium, characterized in that, It contains a computer program that, when executed by a processor, implements the drone swarm target threat assessment method as described in claim 1 or 2.