Name
Title | ||
|---|---|---|
Multisensor adaptive bayesian tracking under time-varying target detection probability. |
Abstract | ||
|---|---|---|
In practical tracking applications, the target detection performance may be unknown and also change rapidly in time. This work considers a network of sensors and develops a target-tracking procedure able to adapt and react to the time-varying changes of the network detection probability. The proposed adaptive tracker is validated using extensive computer simulations and real-world experiments, testing a network of high-frequency radars for maritime surveillance and an underwater network of autonomous underwater vehicles for antisubmarine warfare. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TAES.2016.150522 | IEEE Trans. Aerospace and Electronic Systems |
Keywords | Field | DocType |
Sensors,Target tracking,Radar tracking,Signal to noise ratio,Bayes methods,Object detection,Noise measurement | Computer vision,Object detection,Anti-submarine warfare,Radar tracker,Noise measurement,Tracking system,Artificial intelligence,Low probability of intercept radar,Mathematics,Bayesian probability,Underwater | Journal |
Volume | Issue | ISSN |
52 | 5 | 0018-9251 |
Citations | PageRank | References |
2 | 0.38 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giuseppe Papa | 1 | 2 | 0.38 |
| Paolo Braca | 2 | 467 | 46.44 |
| Steven Horn | 3 | 12 | 2.21 |
| Stefano Marano | 4 | 123 | 9.02 |
| Vincenzo Matta | 5 | 338 | 40.78 |
| Peter Willett | 6 | 1962 | 224.14 |