TY - GEN
T1 - Event-triggered extended Kalman filter for UAV monitoring system
AU - Liu, Yanmin
AU - Liao, Xiaozhong
AU - Wang, Zihao
AU - Chen, Xi
AU - Liu, Xiangdong
AU - Li, Zhen
N1 - Publisher Copyright:
© 2020 IEEE
PY - 2020
Y1 - 2020
N2 - The unmanned aerial vehicles (UAVs) formation needs the frequent data-exchanging of individual's state between units for monitoring and instruction uploading from the ground station, which inevitably occupies huge communication bandwidth. This paper presents the extended Kalman filter (EKF) design based on the event-triggered strategy to get UAVs greatly relieved of the communication burden with guaranteed accuracy. The event-triggered strategy firstly selects only the state measurements containing innovational information for the purpose of filtering. Due to the nonlinearity of UAV system, the EKF is further applied to make full use of the information from the prior event-trigger strategy so as to enhance the performance of estimation. The proposed algorithm is verified on the physical UAVs regarding the estimation quality and communication rate, demonstrating the robust dynamic performance with effectively reduced communication rate.
AB - The unmanned aerial vehicles (UAVs) formation needs the frequent data-exchanging of individual's state between units for monitoring and instruction uploading from the ground station, which inevitably occupies huge communication bandwidth. This paper presents the extended Kalman filter (EKF) design based on the event-triggered strategy to get UAVs greatly relieved of the communication burden with guaranteed accuracy. The event-triggered strategy firstly selects only the state measurements containing innovational information for the purpose of filtering. Due to the nonlinearity of UAV system, the EKF is further applied to make full use of the information from the prior event-trigger strategy so as to enhance the performance of estimation. The proposed algorithm is verified on the physical UAVs regarding the estimation quality and communication rate, demonstrating the robust dynamic performance with effectively reduced communication rate.
KW - Communication rate
KW - Event-trigger strategy
KW - Extended Kalman filter (EKF)
KW - Real-time state estimation
KW - Unmanned aerial vehicles (UAVs)
UR - http://www.scopus.com/inward/record.url?scp=85109346984&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85109346984
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
Y2 - 10 October 2020 through 21 October 2020
ER -