Event-triggered Extended Kalman Filter for UAV Monitoring System

Yunge Zang, Yan Li, Yuting Duan, Xiangyu Li, Xi Chang, Zhen Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

To facilitate ground station monitoring and command uploading, unmanned aerial vehicles (UAVs) need to frequently exchange individual state data between units. However, this results in a significant usage of communication bandwidth. To address this issue, on the basis of an event-triggered strategy, this paper proposes an Extended Kalman Filter (EKF). aimed at reducing the communication burden of UAVs while maintaining high accuracy. Specifically, a state measurement triggered by an event is selected for filtering only if it contains innovation, thereby reducing the amount of data that needs to be communicated. Since UAV systems are nonlinear, EKF is adopted to fully utilize the information obtained from event-triggered strategies, thereby enhancing the estimation performance. In this paper, a physical UAV was used to verify the proposed algorithm, and it proved to have robust dynamic performance and to effectively reduce the communication rate.

源语言英语
主期刊名Proceedings of 2023 IEEE 12th Data Driven Control and Learning Systems Conference, DDCLS 2023
出版商Institute of Electrical and Electronics Engineers Inc.
2032-2036
页数5
ISBN(电子版)9798350321050
DOI
出版状态已出版 - 2023
活动12th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2023 - Xiangtan, 中国
期限: 12 5月 202314 5月 2023

出版系列

姓名Proceedings of 2023 IEEE 12th Data Driven Control and Learning Systems Conference, DDCLS 2023

会议

会议12th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2023
国家/地区中国
Xiangtan
时期12/05/2314/05/23

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