Abstract
This paper focuses on the challenge of estimating the 2D instantaneous ego -motion of vehicles equipped with an automotive radar. To further improve our previous study based on the weighted least squares (wLSQ) method and purpose-designed neural networks (NNs), this work proposes a new network architecture that supports local and global feature extraction as well as point-wise dynamic feature channel mixing. Compared with our previous work, the proposed method provides better estimation accuracy, lighter network size, and faster runtime performance.
| Original language | English |
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| Title of host publication | ICMIM 2024 |
| Subtitle of host publication | International Conference on Microwaves for Intelligent Mobility - 7th IEEE MTT Conference |
| Publisher | VDE Verlag GMBH |
| Pages | 99-102 |
| Number of pages | 4 |
| ISBN (Electronic) | 9783800763641 |
| ISBN (Print) | 978-3-8007-6363-4 |
| Publication status | Published - 2024 |
| Event | 7th IEEE MTT International Conference on Microwaves for Intelligent Mobility, ICMIM 2024 - Boppard, Germany Duration: 16 Apr 2024 → 17 Apr 2024 |
Publication series
| Name | ICMIM 2024: International Conference on Microwaves for Intelligent Mobility - 7th IEEE MTT Conference |
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Conference
| Conference | 7th IEEE MTT International Conference on Microwaves for Intelligent Mobility, ICMIM 2024 |
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| Country/Territory | Germany |
| City | Boppard |
| Period | 16/04/24 → 17/04/24 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.