基于鹰群环伺行为的无人机集群关联跟踪控制

孙永斌; 苏荣茂; 段海滨

doi:10.16383/j.aas.c250518

基于鹰群环伺行为的无人机集群关联跟踪控制

doi: 10.16383/j.aas.c250518

北京航空航天大学自动化科学与电气工程学院飞行器一体化控制全国重点实验室北京 100083

基金项目: 国家自然科学基金 (62473025, 62533006, U2541218, T2121003) 资助

详细信息

作者简介:
孙永斌：北京航空航天大学自动化科学与电气工程学院助理教授. 主要研究方向为无人系统仿生自主控制.E-mail: ybsun@buaa.edu.cn

苏荣茂：北京航空航天大学自动化科学与电气工程学院硕士研究生. 2024年获得天津大学自动化专业学士学位. 主要研究方向为仿生集群自主控制.E-mail: rmsu@buaa.edu.cn

段海滨：北京航空航天大学自动化科学与电气工程学院教授. 主要研究方向为无人机集群仿生自主飞行控制. 本文通信作者.E-mail: hbduan@buaa.edu.cn

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出版历程
- 收稿日期: 2025-09-30
- 录用日期: 2026-02-13
- 网络出版日期: 2026-04-22

Association Tracking Control of UAV Swarms Based on Harris Hawk's Surrounding Behavior

National Key Laboratory of Aircraft Integrated Flight Control, School of Automation Science and Electrical Engineering Beihang University, Beijing 100083

Funds: Supported by National Natural Science Foundation of China (62473025, 62533006, U2541218, T2121003)

More Information

Author Bio:
SUN Yong-Bin Assistant professor at the School of Automation Science and Electrical Engineering, Beihang University. His main research interest is biologically autonomous control of unmanned systems

SU Rong-Mao Master student at the School of Automation Science and Electrical Engineering, Beihang University. He received the bachelor degree in automation from Tianjin University in 2024. His main research interest is autonomous control of bionic swarms

DUAN Hai-Bin Professor at the School of Automation Science and Electrical Engineering, Beihang University. His main research interest is biologically autonomous flight control of unmanned aerial vehicle swarm. Corresponding author of this paper

摘要

摘要: 针对无人机集群在纯方位测量下协同跟踪动态目标集群时面临的强非线性、高维度以及估计-控制耦合等关键难题, 提出一种基于哈里斯鹰群环伺行为的分布式协同估计-控制闭环系统. 基于鹰群在环伺猎物时形成的多视角感知特性, 提出一种方位统计融合估计方法, 将贝叶斯统计与分布式滤波相融合, 引入共视子集的量测结构, 通过伪线性的方位统计降低估计问题中的计算维度,并保持系统的可观性. 依据鹰群的动态封锁机制, 提出一种环伺关联跟踪控制器, 使观测无人机能够主动维持最优环伺态势, 从而提升估计质量及稳定性. 理论分析证明了该闭环系统的Lyapunov稳定性与估计误差的有界性, 数值仿真验证了所提方法的有效性.
- 无人机集群 /
- 协同目标跟踪 /
- 环伺关联跟踪控制 /
- 鹰群环伺行为 /
- 分布式状态估计
Abstract: This paper proposes a distributed estimation–control closed-loop framework for bearing-only cooperative tracking of a dynamic target swarm, inspired by Harris＇s Hawks＇ surrounding behavior. A bearing-statistics fusion estimator is designed by combining Bayesian statistics with distributed filtering, using co-view subsets and pseudo-linearized bearing statistics to reduce computational dimensionality while preserving observability. A surrounding-based correlation tracking controller further enables observer UAVs to maintain an optimal surrounding configuration to enhance estimation quality. Lyapunov analysis establishes closed-loop stability, and simulations validate the effectiveness of the proposed method.
- UAV swarm /
- cooperative target tracking /
- surrounding association tracking control /
- hawks surrounding behavior /
- distributed state estimation

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图 1 哈里斯鹰群环伺行为与无人机集群观测系统的映射关系

Fig. 1 Mapping relationship between Harris Hawks' surrounding behavior and UAV swarm observation system

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图 2 基于鹰群环伺行为的无人机集群关联跟踪控制系统结构图

Fig. 2 Structural diagram of UAV swarm correlation tracking control system based on hawk group's surround behavior

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图 3 目标无人机集群运动轨迹(情况1)

Fig. 3 Target UAV swarm trajectory (case 1)

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图 4 系统跟踪控制轨迹(情况1)

Fig. 4 System tracking control trajectory (Case 1)

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图 6 方位统计融合估计误差(情况1)

Fig. 6 Bearing-only statistical fusion estimation error (Case 1)

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图 5 环伺关联跟踪控制量(情况1)

Fig. 5 Surrounding association tracking control state (Case 1)

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图 7 目标无人机集群运动轨迹(情况2)

Fig. 7 Target UAV swarm trajectory (case 2)

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图 8 系统跟踪控制轨迹(情况2)

Fig. 8 System tracking control trajectory (Case 2)

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图 9 环伺关联跟踪控制量(情况2)

Fig. 9 Surrounding association tracking control state (Case 2)

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图 10 方位统计融合估计误差(情况2)

Fig. 10 Bearing-only statistical fusion estimation error (Case 2)

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