Abstract
The application of distributed radar to human motion monitoring is considered. A novel sensor fusion method has been proposed that yields a two-dimensional map of reflection intensity and a vector field of reconstructed velocities in lieu of conventional Doppler spectrograms or radial velocity components. The method has been verified using experimental datasets in two case studies involving fall detection in sequences of activities, and arm motion discrimination for in-place activities. A true positive rate and precision of respectively 99.3 % and 93.0 % have been demonstrated for the fall detection task, and the output of the proposed method for arm motion characterisation indicates suitability for classification in future research.
| Original language | English |
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| Title of host publication | RadarConf 2024 - 2024 IEEE Radar Conference, Proceedings |
| Publisher | IEEE |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350329209 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 IEEE Radar Conference, RadarConf 2024 - Denver, United States Duration: 6 May 2024 → 10 May 2024 |
Publication series
| Name | Proceedings of the IEEE Radar Conference |
|---|---|
| ISSN (Print) | 1097-5764 |
| ISSN (Electronic) | 2375-5318 |
Conference
| Conference | 2024 IEEE Radar Conference, RadarConf 2024 |
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| Country/Territory | United States |
| City | Denver |
| Period | 6/05/24 → 10/05/24 |
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.
Keywords
- Activity Classification
- Distributed Radar
- Fall Detection
- Human Monitoring
- Sensor Fusion