Abstract
This paper presents an analysis of a new method of automotive radar self-calibration which uses targets of opportunity. While conventional offline calibration of a phased array antenna requires accurate knowledge of the positions of calibration targets relative to the radar, such information is not available in a dynamic scenario. To compensate for this, we have developed an estimation procedure based on an extended Kalman filter (EKF) to address the challenge of simultaneous localisation, mapping and calibration. The proposed technique makes it possible to compensate for moderate errors of amplitude and phase in the phased array response with just a few measured frames. A significant reduction in the sidelobe rejection of the array response, plus the ability to correct for angular steering errors, are demonstrated via numerical simulations and real data processing.
| Original language | English |
|---|---|
| Article number | 9353252 |
| Pages (from-to) | 2062-2075 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 70 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2021 |
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
- calibration
- phased arrays
- Radar
- SLAM