大连海事大学 船舶电气工程学院,辽宁 大连 116026
通信作者邮箱:aliceliujinqi@163.com
收稿:2025-09-04,
网络首发:2026-03-09,
纸质出版:2026-05
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刘津奇, 谭心茹, 郑凯. 基于D-S证据理论的空海跨域无人集群协同效能评估方法[J]. 兵工学报, 2026,47(5):250812.
LIU Jinqi, TAN Xinru, ZHENG Kai. Collaborative Effectiveness Evaluation Method Based on D-S Evidence Theory for Air-sea Cross-domain Unmanned Clusters[J]. Acta Armamentarii, 2026, 47(5): 250812.
刘津奇, 谭心茹, 郑凯. 基于D-S证据理论的空海跨域无人集群协同效能评估方法[J]. 兵工学报, 2026,47(5):250812. DOI: 10.12382/bgxb.2025.0812.
LIU Jinqi, TAN Xinru, ZHENG Kai. Collaborative Effectiveness Evaluation Method Based on D-S Evidence Theory for Air-sea Cross-domain Unmanned Clusters[J]. Acta Armamentarii, 2026, 47(5): 250812. DOI: 10.12382/bgxb.2025.0812.
空海跨域无人集群可有效执行复杂海上任务,系统性的效能评估有助于推动其实战化应用。针对空海跨域无人集群协同效能评估中测量数据具有不确定性的问题,提出了一种基于D-S证据理论的空海跨域无人集群协同效能评估方法。该方法基于OODA作战环理论构建了包含协同侦察感知能力、协同分析判断能力、协同指挥决策能力和协同行动能力四个维度的跨域无人集群协同效能评估指标体系;针对主观赋权法依赖专家经验的问题设计了客观赋权机制,通过Hellinger距离和关联系数构建指标相似度矩阵,形成了考虑指标间相似程度的直接权重与表征指标间相互影响的间接权重相融合的综合权重确定机制,有效捕获了跨域协同过程中指标间的复杂耦合关系;通过隶属度函数对指标数据进行不确定性建模,将各指标看作是印证效能评估结果的证据,从而采用Dempster规则进行融合,得到最终的协同效能评估结果。仿真推演测试结果表明所提出的方法能够实现空海跨域无人集群协同效能评估,在存在数据不确定的情况下提供了一致的评估结果。评估结果可为空海跨域无人集群的作战应用提供参考依据。
Air-sea cross-domain unmanned clusters can effectively execute the complex maritime missions,and the systematic effectiveness evaluation facilitates their operational deployment. An assessment method based on D-S evidence theory is proposed to addresses the challenge of uncertain measurement data in evaluating the collaborative effectiveness of air-sea cross-domain unmanned clusters. This method is used to establishe a four-dimensional index system,which consists of collaborative econnaissance and perception capability,collaborative analysis and judgment capability,collaborative command and decision-making capability,and collaborative action capability,based on OODA theory. An objective weighting mechanism is developed to overcome the limitations of subjective weighting methods that rely heavily on expert experience. An indicator similarity matrix is established by using Hellinger distance and correlation coefficients,whcich integrates direct weights with indirect weights to form a comprehensive weighting determination mechanism that effectively captures complex coupling relationships during cross-domain collaboration. The uncertainty of indicator data is modeled using membership functions,and each indicator is regarded as an evidence corroborating the effectiveness evaluation results. The Dempster combination rule is then applied to fuse this evidence to derive the final results. The results demonstrate that the proposed method can evaluate the collaboration effectiveness of air-sea cross-domain unmanned clusters successfully,and provides consistent assessment outcomes despite the presence of data uncertainty. The evaluation results can serve as a reference basis for the operational application of cross-domain air-sea unmanned clusters.
周栋栋,许登荣,王冰切. 反辐射无人机攻击海上移动目标作战效能评估[J]. 舰船电子对抗, 2021, 44(2): 64 -67, 72.
ZHOU D D, XU D R, WANG B Q. Operational effectiveness evaluation of anti-radiation UAV attacking sea moving targets[J]. Shipboard Electronic Countermeasure, 2021, 44 (2): 64 -67,72.(in Chinese)
潘长鹏,韩玉龙,庄益夫. 舰载无人机编队协同对海突击作战效能评估指标体系研究[J]. 战术导弹技术, 2019(2):25-32.
PAN C P, HAN Y L, ZHUANG Y F. Research on the operational effectiveness evaluation indices system of ship-based UAV formation cooperative air-to-sea attack [J]. Tactical Missile Technology, 2019(2): 25-32.(in Chinese)
JIA N P, YANG Z W, YANG K W. Operational effectiveness evaluation of the swarming UAVs combat system based on a system dynamics model[J]. IEEE Access, 2019, 7: 25209-25224.
夏长俊,洪亮,滕克难. 装备假目标防空作战仿真及效能分析[J]. 海军航空大学学报, 2022, 37(5): 423-428.
XIA C J, HONG L, TENG K N. Combat simulation and effectiveness evaluation of equipment decoys in aerial defence[J]. Journal of Naval Aviation University, 2022, 37(5): 423 -428. (in Chinese)
谷志鸣,高文明,魏潇龙,等. 基于蒙特卡洛法的无人机飞行冲突解脱安全评估[J]. 火力与指挥控制, 2017, 42 (4):158-161.
GUZ M, GAO W M, WEI X L, et al. UAV flight conflict resolution safety assessment technique based on monte Carlo method[J]. Fire Control & Command Control, 2017, 42(4):158-161.(in Chinese)
胡杰,陈化良,刘亮,等. 无人机蜂群作战效能评估研究[J].火力与指挥控制, 2022, 47(4): 164-168.
HU J, CHEN H L, LIU L, et al. Research on operational effectiveness evaluation of UAVswarm [J]. Fire Control&Command Control, 2022, 47(4): 164-168. (in Chinese)
王波,于升涛,孙凯华. 舰载无人机对海突击作战效能评估研究[J]. 无人系统技术, 2023, 6(1): 72-81.
WANG B, YU S T, SUN K H. Research on the effectiveness evaluation of shipborne UAV in sea assault operations [J]. Unmanned Systems Technology, 2023, 6 (1): 72 - 81.( in Chinese)
王晓军,黄沛,唐彬鑫. 基于GA-BP神经网络的无人防空装备作战效能评估[J]. 无人系统技术, 2022, 5(3): 106-113.
WANG X J, HUANG P, TANG B X. Operational effectiveness evaluation of unmanned air defense equipment based on GA-BP neural network [J]. Unmanned Systems Technology, 2022, 5 (3): 106-113.(in Chinese)
陈侠,胡乃宽. 基于改进型支持向量机的侦察无人机作战效能评估[J]. 火力与指挥控制, 2018, 43(10): 31-34.
CHEN X, HU N K. Research on operational effectiveness assessment for reconnaissance UAV based on the improved SVM [J]. Fire Control & Command Control, 2018, 43(10): 31-34. (in Chinese)
赵彬,周中良,阮铖巍,等. 基于灰色模糊贝叶斯网络算法的编队突防作战效能评估方法[J]. 计算机应用, 2017, 37 (增刊1): 356-360, 364.
ZHAO B, ZHOU Z L, RUAN C W, et al. Method of formation penetration operation effectiveness assessment based on gray fuzzy Bayesian network algorithm [J]. Journal of Computer Applications, 2017, 37(S1): 356-360, 364. (in Chinese)
ZENG J J, CHAO H C, WEI J G. Abnormal behavior detection based on D-S evidence theory for air-ground-integrated vehicular networks[J]. IEEE Internet of Things Journal, 2025, 12(9):11347-11355.
LIAO Z R, WANG S P, SHI J, et al. Cooperative situational awareness of multi-UAV system based on improved D-S evidence theory[J]. Aerospace Science and Technology, 2023, 142(Part A): 108605.
YANG X, XIAO F Y. A novel uncertainty modeling method in complex evidence theory for decision making [J]. Engineering Applications of Artificial Intelligence, 2024, 133 ( Part C):108164.
ZHOU N, XU Y. A multi-evidence fusion based integrated method for health assessment of medium voltage switchgears in power grid[J]. IEEE Transactions on Power Delivery, 2023, 38 (2): 1406-1415.
陈清霖,田鸿堂,王鹏,等. 基于“OODA”环的分布式协同作战武器编配方案[J]. 兵工学报, 2021, 42(8): 1780 -1788.
CHEN Q L, TIAN H T, WANG P, et al. A collocation scheme of distributed cooperative operational weapons based on OODA loop[J]. Acta Armamentarii, 2021, 42(8): 1780 -1788. (in Chinese)
SHEN B, WU W L, YANG G, et al. Evaluation models and methods for intelligence of unmanned swarm systems based on collective OODA loop [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(14): 328003.
王翀,倪海参,王赢旋,等. 基于GA-BP神经网络的多无人艇协同作战效能评估[J]. 舰船科学技术, 2024, 46(1):109-114.
WANG C, NI H S, WANG Y X, et al. Effectiveness evaluation for multiple unmanned surface vehicles cooperative combat based on GA-BP neural network[J]. Ship Science and Technology, 2024, 46(1): 109-114. (in Chinese)
党晨光,李超,封慧勇,等. 陆空无人集群协同作战效能评估[J]. 兵器装备工程学报, 2025, 46(8): 53-59.
DANG C G, LI C, FENG H Y, et al. Evaluation of the effectiveness of air-ground unmanned swarm cooperative operations[J]. Journal of Ordnance Equipment Engineering, 2025, 46(8): 53-59. (in Chinese)
TANG Y C, WU K K, LI R F, et al. Probabilistic transformation of basic probability assignment based on weighted visibility graph networks[J]. Applied Soft Computing, 2025, 184 ( Part B):113821.
GUAN X, YU H T, YI X. Optimized methods for basic probability assignments in evidence theory: applications to fault diagnosis[J]. Engineering Applications of Artificial Intelligence, 2025, 160(Part A): 111737.
JIANG W, DENG Y. Evaluating and sequencing of the air target threat based on Dempster-Shafer evidence theory [C]//Proceedings of the 2010 Third International Symposium on Information Science and Engineering. Shanghai, CN: IEEE, 2010: 349-353.
LIU X Y, LIU S L, XIANG J W, et al. A conflict evidence fusion method based on the composite discount factor and the game theory[J]. Information Fusion, 2023, 94: 1-16.
于冰倩,李学艳,程思齐,等. 基于复杂网络的陆空协同作战体系效能评估方法[J]. 火力与指挥控制, 2024, 49(1):105-110.
YU B Q, LI X Y, CHENG S Q, et al. A method for evaluating the effectiveness of land-air collaborative warfare system based on complex networks[J]. Fire Control & Command Control, 2024, 49(1): 105-110.(in Chinese)
唐军军,吴健,丁林飞,等. 无人集群复杂网络建模及其作战任务可靠性评估[J]. 火力与指挥控制, 2025, 50(2):78-85.
TANG J J, WU J, DING L F, et al. Unmanned swarms complex network modeling and operational mission reliability evaluation [J]. Fire Control & Command Control, 2025, 50(2): 78-85.(in Chinese)
ZHU C S, XIAO F Y. A belief Hellinger distance for D-S evidence theory and its application in pattern recognition [J]. Engineering Applications of Artificial Intelligence, 2021, 106:104452.
DENG Y, SHI W K, ZHU Z F, et al. Combining belief functions based on distance of evidence [J]. Decision Support Systems, 2004, 38(3): 489-493.
XIONG L H, SU X Y, QIAN H. Conflicting evidence combination from the perspective of networks [J]. Information Sciences, 2021, 580: 408-418.
李鹏翔,任玉晴,席酉民. 网络节点(集)重要性的一种度量指标[J]. 系统工程, 2004, 22(4): 13-20.
LIPX,RENYQ,XIYM. An importance measure of actors (set) within a network [J]. Systems Engineering, 2004, 22 (4): 13-20.(in Chinese)
黄杰,袁俊,崔翛龙,等. 基于层次分析法和模糊评价方法相结合的装备数据评估模型方法研究[J]. 网络安全与数据治理, 2024, 43(11): 43-49, 55.
HUANG J, YUAN J, CUI X L, et al. Research on evaluation for equipment data based on the combination of analytic hierarchy process and fuzzy comprehensive evaluation[J]. Cyber Security and Data Governance, 2024, 43 (11 ): 43 - 49, 55.( in Chinese)
王希,周林,王小龙. 基于云重心评判法的测控装备运维保障效能评估[J]. 装甲兵学报, 2023(2): 65-69.
WANG X, ZHOU L, WANG X L. Evaluation of operation and maintenance support effectiveness of measurement and control equipment based on cloud center of gravity evaluation method [J]. Journal of Armored Forces, 2023 (2): 65 - 69. ( in Chinese)
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