Name
Title | ||
|---|---|---|
Innovative Interaction Approach in IMM Filtering for Vehicle Motion Models With Unequal States Dimension |
Abstract | ||
|---|---|---|
Robust and adaptive vehicle state estimation and tracking algorithms have become a very important part within the autonomous driving field. The family of interacting multiple model (IMM) filters has shown to provide very effective and accurate state estimation in systems whose behavior patterns change significantly over time. The main reason for the improved performance of IMM filters compared to ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TVT.2022.3146626 | IEEE Transactions on Vehicular Technology |
Keywords | DocType | Volume |
State estimation,Filtering algorithms,Tracking,Data models,Autonomous vehicles,Noise measurement,Motion estimation | Journal | 71 |
Issue | ISSN | Citations |
4 | 0018-9545 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jasmina Zubaca | 1 | 0 | 1.01 |
| Michael Stolz | 2 | 0 | 0.34 |
| Richard Seeber | 3 | 24 | 9.22 |
| Markus Schratter | 4 | 0 | 0.34 |
| Daniel Watzenig | 5 | 0 | 0.68 |