Title :
Distributed Estimation for Moving Target Based on State-Consensus Strategy
Author :
Zhenwei Zhou ; Haitao Fang ; Yiguang Hong
Author_Institution :
Key Lab. of Syst. & Control, Acad. of Math. & Syst. Sci., Beijing, China
Abstract :
This technical note studies the distributed estimation problem for a continuous-time moving target under switching interconnection topologies. A recursive distributed estimation algorithm is proposed by using state-consensus strategy, where a common gain is assigned to adjust the innovative and state-consensus information for each sensor in the network. Under mild conditions on observability and connectivity, the stability of the distributed estimation algorithm is analyzed. An upper bound and lower bound for the total mean square estimation error (TMSEE) are obtained by virtue of the common Lyapunov method and Kalman-Bucy filtering theory, respectively. Then a numerical simulation is given to verify the effectiveness of the proposed algorithm.
Keywords :
Lyapunov methods; distributed algorithms; filtering theory; graph theory; mean square error methods; observability; Kalman-Bucy filtering theory; TMSEE lower bound; TMSEE upper bound; common Lyapunov method; common gain; connectivity condition; continuous-time moving target; distributed estimation; distributed estimation problem; numerical simulation; observability condition; recursive distributed estimation algorithm; state-consensus strategy; switching interconnection topology; total mean square estimation error; Estimation; Kalman filters; Noise; Standards; Switches; Topology; Upper bound; Distributed estimation; Kalman-Bucy filter; moving target; stability; switching topologies;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2013.2246476
