1. 西北工业大学航海学院,陕西,西安,710072
2. 中国船舶集团有限公司系统工程研究院,北京,100094
3. 西北工业大学宁波研究院,浙江,宁波,315103
收稿:2025-06-30,
网络首发:2026-03-09,
移动端阅览
邹秉运,姜丽伟,彭星光. 有限感知下的集群自组织边界防御策略[J/OL]. 兵工学报, 2026(2026-03-09). https://doi.org/10.12382/bgxb.2025.0577.
ZOU B Y, JIANG L W, PENG X G. A self-organized perimeter defense strategy for swarms under limited perception[J/OL]. Acta Armamentarii, 2026(2026-03-09). https://doi.org/10.12382/bgxb.2025.0577. (in Chinese)
邹秉运,姜丽伟,彭星光. 有限感知下的集群自组织边界防御策略[J/OL]. 兵工学报, 2026(2026-03-09). https://doi.org/10.12382/bgxb.2025.0577. DOI:
ZOU B Y, JIANG L W, PENG X G. A self-organized perimeter defense strategy for swarms under limited perception[J/OL]. Acta Armamentarii, 2026(2026-03-09). https://doi.org/10.12382/bgxb.2025.0577. (in Chinese) DOI:
针对通信受限、高动态环境下无人集群边界防御中攻击者序列高效拦截问题,提出一种基于有限感知的集群自组织防御策略。该策略无需显式通信与中心式指控,防御个体仅依赖局部方位及距离量测信息进行分布式决策。通过理论推导确定完全覆盖边界所需的最小防御数量,支撑系统部署;面向防御个体视角构建目标选择机制,结合相对距离、方位及密集程度评估威胁态势,并利用占优可达集划分规避选择冲突;引入马尔可夫链模型实现边界均匀覆盖策略与入侵拦截策略的自适应切换,平衡即时拦截与边界覆盖。仿真表明,在攻击者数量显著多于防御者时,该策略仍能稳定拦截攻击序列,当防御规模且攻击间隔适中时,拦截成功率可达95%以上;相较分区式最大路径算法拦截效率更高,且在中等规模优势更明显。在椭圆与圆角矩形等规则边界下性能稳定;在S型机动攻击下效率有所下降,但可通过增加防御规模与覆盖密度进行补偿,体现出良好的鲁棒性与可扩展性。
To address the problem of efficient interception of sequential intrusions inperimeterdefense for unmanned swarms under communication constraints and highly dynamic environments
this paper proposes a self-organized defense strategy based on limited sensing. The proposed strategy requires neither explicit inter-agent communication nor centralized command and control; instead
each defender makes distributed decisions using only local measurements of relative bearing and distance. A theoretical analysis is conducted to derive the minimum number of defenders needed to fully cover theperimeter
providing guidance for deployment. From an individual-defender perspective
a target-selection mechanism is developed by evaluating threat levels using relative distance
relative bearing
and local density
and conflicts are mitigated through dominant reachable-set partitioning. In addition
a Markov-chain-based framework is introduced to enable adaptive switching between uniformperimeter-coverage and intrusion-interception behaviors
balancing immediate interception performance withperimeterintegrity.Simulation results demonstrate that
even when the number of attackers is significantly larger than that of defenders
the proposed strategy can stably intercept sequential attacks; under moderate defender scale and attack-release intervals
the interception success rate exceeds 95%. Compared with partition-based longest-path methods
it achieves higher interception efficiency
with more pronounced advantages at medium swarm sizes. The strategy also maintains stable performance under regular noncircular boundaries such as ellipses and rounded rectangles. Although the interceptionefficiency decreases under S-shaped maneuvering attacks
the performance loss can be compensated by increasing the number of defenders andperimetercoverage density
indicating strong robustness and scalability.
王莉. 人工智能在军事领域的渗透与应用思考[J]. 科技导报, 2017, 35(15): 15-19. WANG L. Penetration and application of artificial intelligence into military field[J]. Science & Technology Review, 2017, 35(15): 15-19. (in Chinese).
李军, 陈士超. 无人机蜂群关键技术发展综述[J]. 兵工学报, 2023, 44(9): 2533-2545. LI J, CHEN S C. Overview of key technology and its development of drone swarm[J]. Acta Armamentarii, 2023, 44(9): 2533−2545. (in Chinese).
THOMAS T. Russian Lessons Learned in Syria: An Assessment[R]. Bedford: The MITRE Corporation, 2020.
VOSKUIJL M, DEKKERS T, SAVELSBERG R. Flight performance analysis of the samad attack drones operated by Houthi armed forces[J]. Science & Global Security, 2020, 28(3): 113-134.
刘施阳, 师帅. 纳卡冲突中无人机的应用与启示[J]. 兵工自动化, 2021, 40(11): 43-45,59. LIU S Y, SHI S. Application and enlightenment of unmanned aerial vehicles in the Nagorno-Karabakh conflict[J]. Ordnance Industry Automation, 2021, 40(11): 43-45,59. (in Chinese).
王童豪, 彭星光, 胡浩, 等. 海上有人/无人协同系统及其关键技术综述[J]. 兵工学报, 2024, 45(10): 3317-3340. WANG T H, PENG X G, HU H, et al. Maritime Manned / unmanned Collaborative Systems and Key Technologies: A Survey[J]. Acta Armamentarii, 2024, 45(10): 3317−3340. (in Chinese).
孔国杰, 冯时, 于会龙, 等. 无人集群系统协同运动规划技术综述[J]. 兵工学报, 2023, 44(1): 11-26. KONG G J, FENG S, YU H L, et al. A review on cooperative motion planning of unmanned vehicles[J]. Acta Armamentarii, 2023, 44(1): 11−26. (in Chinese).
DAS G, DOROTHY M, BELL Z I, et al. Defending a static target point with a slow defender[C]// Proceedings of the 43rd American Control Conference (ACC). [S.l.]: IEEE, 2024: 4064-4071.
RUAN W, SUN Y, DENG Y, et al. Hawk-pigeon game tactics for unmanned aerial vehicle swarm target defense[J]. IEEE Transactions on Industrial Informatics, 2023, 19(12): 11619-11629.
FRANCOS R M, BRUCKSTEIN A M. Defense against smart invaders with swarms of sweeping agents[J]. Robotics and Autonomous Systems, 2024, 173: 104620.
ENGLISH J T, WILHELM J P. Defender-Aware Attacking Guidance Policy for the Target–Attacker–Defender Differential Game[J]. Journal of Aerospace Information Systems, 2021, 18(6): 366-376.
SHISHIKA D, KUMAR V. A review of multi agent perimeter defense games[C]. ZHU Q, BARAS J S, POOVENDRAN R, et al., eds.// Proceedings of the 11th International Conference on Decision and Game Theory for Security. Cham: Springer International Publishing, 2020: 472-485.
朱建文, 赵长见, 李小平, 等. 基于强化学习的集群多目标分配与智能决策方法[J]. 兵工学报, 2021, 42(9): 2040-2048. ZHU J W, ZHAO C J, LI X P, et al. Multi-target assignment and intelligent decision based on reinforcement learning[J]. Acta Armamentarii, 2021, 42(9): 2040−2048. (in Chinese).
SHISHIKA D, KUMAR V. Local-game decomposition for multiplayer perimeter-defense problem[C]// Proceedings of 2018 IEEE 57th Conference on Decision and Control (CDC). [S.l.]: IEEE, 2018: 2093-2100.
SHISHIKA D, PAULOS J, KUMAR V. Cooperative team strategies for multi-player perimeter-defense games[J]. IEEE Robotics and Automation Letters, 2020, 5(2): 2738-2745.
SHISHIKA D, PAULOS J, DOROTHY M R, et al. Team composition for perimeter defense with patrollers and defenders[C]// Proceedings of 2019 IEEE 58th Conference on Decision and Control (CDC). [S.l.]: IEEE, 2019: 7325-7332.
何子琦, 李博宸, 王成罡, 等. 针对区域防御的多无人机序列捕捉算法[J]. 兵工学报, 2025, 46(4): 281-293. HE Z Q, LI B C, WANG C G, et al. Multi-UAV sequential capture algorithm for area defense[J]. Acta Armamentarii, 2025, 46(4): 281−293. (in Chinese).
VELHAL S, SUNDARAM S, SUNDARARAJAN N. A decentralized multirobot spatiotemporal multitask assignment approach for perimeter defense[J]. IEEE Transactions on Robotics, 2022, 38(5): 3085-3096.
MACHARET D G, CHEN A K, SHISHIKA D, et al. Adaptive partitioning for coordinated multi-agent perimeter defense[C]// Proceedings of the 33rd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). [S.l.]: IEEE, 2020: 7971-7977.
BAJAJ S, BOPARDIKAR S D, TORNG E, et al. Multivehicle perimeter defense in conical environments[J]. IEEE Transactions on Robotics, 2024, 40: 1439-1456.
ADLER A, MICKELIN O, RAMACHANDRAN R K, et al. The role of heterogeneity in autonomous perimeter defense problems[J]. International Journal of Robotics Research, 2024, 43(9): 1363-1381.
BAJAJ S, BOPARDIKAR S D. Dynamic boundary guarding against radially incoming targets[C]// Proceedings of 2019 IEEE 58th Conference on Decision and Control (CDC). [S.l.]: IEEE, 2019: 4804-4809.
SMITH S L, BOPARDIKAR S D, BULLO F. A dynamic boundary guarding problem with translating targets[C] //Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chinese Control Conference. [S.l.]: IEEE, 2009: 8543-8548.
0
浏览量
0
下载量
0
CNKI被引量
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024360号