Name
Abstract | ||
|---|---|---|
This paper addresses the problem of simultaneously localizing multiple targets and estimating the positions of the sensors in a sensor network using particle filters. We develop a new technique called multitarget simultaneous localization and mapping (MSLAM) that has better performance than the well-known FastSLAM when there are several targets in the surveillance area. The proposed algorithm is based on the parallel partition particle filter, especially designed for multiple target tracking, and the truncated unscented Kalman filter for updating the sensors' positions. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TSP.2011.2160862 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
parallel partition particle filter,Sensor Network,truncated unscented Kalman filter,Multitarget Simultaneous Localization,multiple target,sensor network,multitarget simultaneous localization,particle filter,proposed algorithm,better performance,multiple target tracking,new technique | Computer vision,Control theory,Particle filter,Kalman filter,Atmospheric measurements,Artificial intelligence,Partition (number theory),Simultaneous localization and mapping,Wireless sensor network,Trajectory,Mathematics | Journal |
Volume | Issue | ISSN |
59 | 10 | 1053-587X |
Citations | PageRank | References |
4 | 0.43 | 28 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angel F. Garcia-Fernandez | 1 | 131 | 18.15 |
| Mark R. Morelande | 2 | 195 | 24.96 |
| Jesús Grajal | 3 | 100 | 13.47 |