Name
Abstract | ||
|---|---|---|
In this paper, a distributed ensemble Kalman filter (DEnKF) is proposed for sensor fusion in a sensor network. To solve data fusion problem in distributed sensor network, consensus filter is implemented. To estimates nodes' states, each node uses local and neighbors' information rather than the information from all nodes in the network. So, due to this property, this proposed algorithm is applicable to large scale problem. Simulation results demonstrate the effectiveness of DEnKF algorithm. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IRI.2013.6642544 | Information Reuse and Integration |
Keywords | Field | DocType |
Kalman filters,sensor fusion,DEnKF,consensus filter,data fusion problem,distributed ensemble Kalman filter,distributed sensor network,large scale problem,multisensor application,sensor fusion,consensus filter,distributed ensemble Kalman filter,sensor fusion | Extended Kalman filter,Alpha beta filter,Fast Kalman filter,Computer science,Covariance intersection,Kalman filter,Sensor fusion,Artificial intelligence,Ensemble Kalman filter,Invariant extended Kalman filter,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Kazerooni | 1 | 0 | 0.34 |
| Faridoon Shabaninia | 2 | 21 | 6.74 |
| Mohammad Vaziri | 3 | 11 | 3.96 |
| Suresh Vadhva | 4 | 12 | 4.36 |