Name
Abstract | ||
|---|---|---|
We consider the distributed tracking problem in networks of heterogeneous agents with limited sensing and communication ranges. A gossip-based distributed Kalman filter (GDKF) is proposed, where an average consensus on predictions of different agents is achieved by randomized, asynchronous gossip algorithms in a totally distributed way. The error dynamics of GDKF is proved to be a globally asymptotically stable system and the error reduction rate is provided. To demonstrate the improved performance of GDKF, we compare it with an alternative distributed estimation strategy termed Kalman-Consensus Filter (KCF) by implementing them to track a maneuvering target collectively with heterogeneous agents. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LCOMM.2016.2637889 | IEEE Communications Letters |
Keywords | Field | DocType |
Target tracking,Sensors,Kalman filters,Estimation,Handover,Noise measurement | Asynchronous communication,Extended Kalman filter,Noise measurement,Computer science,Gossip,Kalman filter,Invariant extended Kalman filter,Handover,Stability theory,Distributed computing | Journal |
Volume | Issue | ISSN |
21 | 4 | 1089-7798 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kangjian Ma | 1 | 0 | 0.34 |
| Shaochuan Wu | 2 | 18 | 6.51 |
| Yuming Wei | 3 | 7 | 2.85 |
| Wenbin Zhang | 4 | 1 | 1.03 |