Name
Abstract | ||
|---|---|---|
This paper considers extended object tracking (EOT) using high-resolution automotive radar measurements with online spatial model adaptation. This is motivated by the fact that offline learned spatial models may be over-smoothed due to coarsely labeled training data and can be mismatched to onboard radar sensors due to different specifications. To refine the offline learned spatial representation ... |
Year | Venue | Keywords |
|---|---|---|
2021 | 2021 IEEE 24th International Conference on Information Fusion (FUSION) | Adaptation models,Radar measurements,Training data,Radar,Predictive models,Radar tracking,Numerical models |
DocType | ISBN | Citations |
Conference | 978-1-7377497-1-4 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gang Yao | 1 | 0 | 0.34 |
| Pu Wang | 2 | 0 | 1.35 |
| Karl Berntorp | 3 | 0 | 1.01 |
| Hassan Mansour | 4 | 0 | 0.68 |
| Petros Boufounos | 5 | 0 | 0.68 |
| Petros T. Boufounos | 6 | 828 | 56.77 |