Resilient Unscented Kalman Filtering Fusion With Dynamic Event-Triggered Scheme: Applications to Multiple Unmanned Aerial Vehicles

In this article, the resilient unscented Kalman filtering fusion issue is investigated for a class of nonlinear systems under the dynamic event-triggered mechanism where each sensor node transmits the measurement information to its corresponding local filter in an intermittent way. Compared with its...

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Bibliographic Details
Published inIEEE transactions on control systems technology Vol. 31; no. 1; pp. 370 - 381
Main Authors Li, Chunyu, Wang, Zidong, Song, Weihao, Zhao, Shixin, Wang, Jianan, Shan, Jiayuan
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Autonomous aerial vehicles
Covariance
Data communication
Data transmission
Dynamic event-triggered mechanism
Dynamic scheduling
Energy consumption
fusion estimation
Kalman filters
Location awareness
Maneuvering targets
multiple unmanned aerial vehicles (UAVs)
Nonlinear systems
Numerical simulation
resilient filtering
Tracking
Unmanned aerial vehicles
unscented Kalman filtering
Vehicle dynamics
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Summary:In this article, the resilient unscented Kalman filtering fusion issue is investigated for a class of nonlinear systems under the dynamic event-triggered mechanism where each sensor node transmits the measurement information to its corresponding local filter in an intermittent way. Compared with its static counterpart, the dynamic event-triggered scheme is capable of scheduling the frequency of data transmission in a more efficient way, thereby better reducing communication burden and energy consumption. In addition, for each local filter, the variation of the filter gain is characterized by a multiplicative noise term. To cope with the intractable problem of computing the cross covariance between local filters, the sequential covariance intersection fusion strategy is introduced into the proposed distributed fusion framework. Finally, the proposed algorithm is applied to a maneuvering target tracking scenario with multiple unmanned aerial vehicles, and both numerical simulations and hardware experiments are provided to elucidate the effectiveness and practicality of the proposed filtering scheme.
ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2022.3180942