Name
Abstract | ||
|---|---|---|
In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19092003 | SENSORS |
Keywords | Field | DocType |
Doppler data association (DDA),Doppler measurement,kinematic state estimation,multi-target tracking,tracking performance | Computer vision,Kinematics,Wireless,Marine mammals and sonar,Linear filter,Electronic engineering,Sonar,Artificial intelligence,Probabilistic logic,Engineering,Doppler effect,Underwater | Journal |
Volume | Issue | ISSN |
19 | 9.0 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Yao | 1 | 2 | 1.72 |
| Zhao Junhui | 2 | 139 | 19.70 |
| Lenan Wu | 3 | 700 | 62.18 |