Name
Title | ||
|---|---|---|
Approximate distributed Kalman filtering in sensor networks with quantifiable performance |
Abstract | ||
|---|---|---|
We analyze the performance of an approximate distributed Kalman filter proposed in recent work on distributed coordination. This approach to distributed estimation is novel in that it admits a systematic analysis of its performance as various network quantities such as connection density, topology, and bandwidth are varied. Our main contribution is a frequency-domain characterization of the distributed estimator's steady-state performance; this is quantified in terms of a special matrix associated with the connection topology called the graph Laplacian, and also the rate of message exchange between immediate neighbors in the communication network. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/IPSN.2005.1440912 | IPSN |
Keywords | Field | DocType |
Kalman filters,approximation theory,distributed sensors,frequency-domain analysis,graph theory,matrix algebra,telecommunication network topology,approximate distributed Kalman filter,connection topology,distributed coordination,frequency-domain characterization,graph Laplacian matrix,message exchange,quantifiable performance,sensor network,steady-state performance | Graph theory,Laplacian matrix,Topology,Telecommunications network,Computer science,Approximation theory,Real-time computing,Kalman filter,Bandwidth (signal processing),Wireless sensor network,Estimator,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-7803-9201-9 | 82 | 15.17 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Demetri P. Spanos | 1 | 114 | 17.17 |
| Reza Olfati-Saber | 2 | 8066 | 549.43 |
| Richard M. Murray | 3 | 12322 | 1223.70 |