Abstract
The problem of localization of targets and determining their velocities by means of radar is formulated as a joint estimation problem over single, three-dimensional domain. Joint estimation algorithms remove problems with data association and allow to exploit relations between individual estimation problems. To exploit wide bandwidth of the sensing signals, a new signal
model is formulated based on time-dependant steering vectors for wideband automotive LFMCW radar applications. Joint three dimensional range-azimuth-Doppler estimation is performed using MUSIC approach based on the proposed signal model. The signal model is further improved based on investigation of inter-pulse Doppler effects on the radar array. Results of proposed model are compared to narrow-band MUSIC based joint estimation
approach.
model is formulated based on time-dependant steering vectors for wideband automotive LFMCW radar applications. Joint three dimensional range-azimuth-Doppler estimation is performed using MUSIC approach based on the proposed signal model. The signal model is further improved based on investigation of inter-pulse Doppler effects on the radar array. Results of proposed model are compared to narrow-band MUSIC based joint estimation
approach.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 14th European Radar Conference |
| Place of Publication | Piscataway, NJ |
| Publisher | IEEE |
| Pages | 73-76 |
| Number of pages | 4 |
| ISBN (Electronic) | 978-2-87487-049-1 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 14th European Radar Conference, EuRAD 2017 - Nuremberg, Germany Duration: 11 Oct 2017 → 13 Oct 2017 http://www.eumweek.com/conferences/eurad.html |
Conference
| Conference | 14th European Radar Conference, EuRAD 2017 |
|---|---|
| Abbreviated title | EuRAD-2017 |
| Country/Territory | Germany |
| City | Nuremberg |
| Period | 11/10/17 → 13/10/17 |
| Internet address |
Keywords
- Estimation
- Radar
- Azimuth
- Direction-of-arrival estimation
- Multiple signal classification
- Covariance matrices
- Signal to noise ratio
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