考虑扰动的无人机集群协同态势感知一致性评估

唐帅文; 周志杰; 姜江; 曹友; 陈媛; 叶燕清

doi:10.7527/S1000-6893.2020.24233

航空学报 >

2020 , Vol. 41 >Issue S2: 724233 - 724233

DOI: https://doi.org/10.7527/S1000-6893.2020.24233

考虑扰动的无人机集群协同态势感知一致性评估

唐帅文 ,
周志杰 ,
姜江 ,
曹友 ,
陈媛 ,
叶燕清

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1. 火箭军工程大学导弹工程学院, 西安 710025;
2. 国防科技大学系统工程学院, 长沙 410073

收稿日期: 2020-05-18

修回日期: 2020-06-01

网络出版日期: 2020-06-12

基金资助

国家自然科学基金（61773388，61751304）

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Consensus evaluation of UAV swarm cooperative situation awareness considering perturbation

TANG Shuaiwen ,
ZHOU Zhijie ,
JIANG Jiang ,
CAO You ,
CHEN Yuan ,
YE Yanqing

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1. School of Missile Engineering, Rocket Force University of Engineering, Xi'an 710025, China;
2. School of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Received date: 2020-05-18

Revised date: 2020-06-01

Online published: 2020-06-12

Supported by

National Natural Science Foundation of China (61773388, 61751304)

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摘要

无人机（UAV）集群协同态势感知（SA）一致性是无人机集群协同作战的关键，对一致性进行评估至关重要。针对态势感知过程中面临的强不确定性等问题，在一致性评估指标体系的基础上，提出了基于证据推理规则的态势感知一致性评估方法，将各类指标信息统一至置信结构，并充分考虑指标的权重与可靠度。采用扰动分析法对复杂战场环境进行模拟，提出考虑扰动的态势感知一致性评估方法，并对算法进行了总结。最后，通过仿真算例和对比研究验证了所提方法在不确定性表达、一致性评估和无人机集群的环境适应性研究等方面的有效性。

关键词： 无人机集群; 态势感知; 一致性评估; 证据推理规则; 扰动分析

本文引用格式

唐帅文 , 周志杰 , 姜江 , 曹友 , 陈媛 , 叶燕清 . 考虑扰动的无人机集群协同态势感知一致性评估[J]. 航空学报, 2020 , 41(S2) : 724233 -724233 . DOI: 10.7527/S1000-6893.2020.24233

Abstract

Cooperative Situation Awareness (SA) consensus of Unmanned Aerial Vehicle (UAV) swarms is the key to UAV swarm cooperative operations, and therefore it is exceedingly significant to evaluate the consensus. Aiming at the problem of strong uncertainties in the SA process, and based on the consensus evaluation index system, this paper proposes an evidential reasoning rule based consensus evaluation method, where all the index information can be unified into a belief structure, and the weight and reliability of the index are fully considered. The perturbation analysis is employed to simulate the complex operational environment, and a consensus evaluation method of SA considering perturbations is proposed, followed by a summary of the algorithm. Finally, the effectiveness of the proposed method in the uncertainty expression, consensus evaluation and research on the environment adaptability of UAV swarms is verified by a simulation example and a comparative study.

Key words： UAV swarms; situation awareness; consensus evaluation; evidential reasoning rule; perturbation analysis

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