TY - GEN
T1 - Distributed Information Filter for Linear Systems with Colored Measurement Noise
AU - Yang, Yanbo
AU - Qin, Yuemei
AU - Pan, Quan
AU - Yang, Yanting
AU - Li, Zhi
N1 - Publisher Copyright:
© 2019 ISIF-International Society of Information Fusion.
PY - 2019/7
Y1 - 2019/7
N2 - This paper considers the distributed filtering problem for discrete-time linear systems with colored measurement noise obeying an autoregressive process in sensor networks. For the considered system in the centralized fusion framework, a novel information-type filter is proposed based on the measurement difference approach. Here, the dimension of the estimate error covariance (i.e., the information matrix) in the proposed information filter is the same as that of the original system state, with the help of the block matrix inverse operation. Then, the average consensus-based distributed implementation is designed, to ensure that the final state estimate in each sensor node is asymptotically consistent with the centralized filtering result as closely as possible. An example about target tracking with colored measurement noise in sensor networks validates the proposed method.
AB - This paper considers the distributed filtering problem for discrete-time linear systems with colored measurement noise obeying an autoregressive process in sensor networks. For the considered system in the centralized fusion framework, a novel information-type filter is proposed based on the measurement difference approach. Here, the dimension of the estimate error covariance (i.e., the information matrix) in the proposed information filter is the same as that of the original system state, with the help of the block matrix inverse operation. Then, the average consensus-based distributed implementation is designed, to ensure that the final state estimate in each sensor node is asymptotically consistent with the centralized filtering result as closely as possible. An example about target tracking with colored measurement noise in sensor networks validates the proposed method.
KW - average consensus
KW - block matrix inverse
KW - colored measurement noise
KW - distributed filtering
KW - information filtering
UR - https://www.scopus.com/pages/publications/85081788676
M3 - 会议稿件
AN - SCOPUS:85081788676
T3 - FUSION 2019 - 22nd International Conference on Information Fusion
BT - FUSION 2019 - 22nd International Conference on Information Fusion
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Information Fusion, FUSION 2019
Y2 - 2 July 2019 through 5 July 2019
ER -