TY - GEN
T1 - Stochastic Stability of Distributed Extended Kalman Filter with Consensus on Estimates
AU - Chen, Lepeng
AU - Cui, Rongxin
AU - Yan, Weisheng
N1 - Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - One of the most important problems in multisensor system is to estimate the states of targets, and Kalman filtering is one of the effective algorithms for estimating. In this paper, we reveal the error behavior of a distributed extended Kalman Filter (DEKF) that consensus on state estimations for general discrete-time nonlinear systems. Under certain conditions and appropriately choosing the adjustable consensus gain, we employ Lyapunov techniques to prove that all estimation errors remain bounded and all estimators converge to a consensus on state estimates. Furthermore, several lemmas are introduced to support the Lyapunov stability analysis.
AB - One of the most important problems in multisensor system is to estimate the states of targets, and Kalman filtering is one of the effective algorithms for estimating. In this paper, we reveal the error behavior of a distributed extended Kalman Filter (DEKF) that consensus on state estimations for general discrete-time nonlinear systems. Under certain conditions and appropriately choosing the adjustable consensus gain, we employ Lyapunov techniques to prove that all estimation errors remain bounded and all estimators converge to a consensus on state estimates. Furthermore, several lemmas are introduced to support the Lyapunov stability analysis.
UR - https://www.scopus.com/pages/publications/85052550540
U2 - 10.23919/ACC.2018.8430766
DO - 10.23919/ACC.2018.8430766
M3 - 会议稿件
AN - SCOPUS:85052550540
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 1021
EP - 1026
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -