Name
Abstract | ||
|---|---|---|
We propose and study a new distributed Kalman filter algorithm that can track unstable dynamics with bounded mean-squared error (MSE). The Network Tracking Capacity (NTC) of this algorithm depends only on the diffusion rate of the network and is independent of the local observation patterns, only requiring global observability. We analyze and compare the NTC for different network models. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACSSC.2013.6810357 | Pacific Grove, CA |
Keywords | Field | DocType |
Kalman filters,mean square error methods,object tracking,observability,MSE,NTC,bounded mean-squared error,distributed Kalman filter algorithm,global observability,network tracking capacity,observation patterns | Extended Kalman filter,Mathematical optimization,Observability,Fast Kalman filter,Control theory,Computer science,Symmetric matrix,Kalman filter,Network model,Kalman filter algorithm,Bounded function | Conference |
ISSN | ISBN | Citations |
1058-6393 | 978-1-4799-2388-5 | 2 |
PageRank | References | Authors |
0.42 | 8 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Subhro Das | 1 | 59 | 5.63 |
| José M. F. Moura | 2 | 5137 | 426.14 |