TY - GEN
T1 - Algorithmic steps for SAR backprojection on radar based motion estimation
AU - Gisder, Thomas
AU - Meinecke, Marc Michael
AU - Biebl, Erwin
N1 - Publisher Copyright:
© 2020 Warsaw University of Technology.
PY - 2020/10/5
Y1 - 2020/10/5
N2 - When adapting SAR (synthetic aperture radar) techniques to vehicles it becomes obvious, that there are some dramatic differences to air-born SAR systems. The main difference in automotive applications is, that vehicles does not drive with constant speed in straight direction only as planes do. Therefore in this paper a novel algorithm is developed what enables to estimate vehicles ego motion very precisely and at exactly those time steps when it is needed. This algorithm enables both, generating SAR maps as well as autarkic ego motion estimation. Tests in real traffic scenarios show promising results.
AB - When adapting SAR (synthetic aperture radar) techniques to vehicles it becomes obvious, that there are some dramatic differences to air-born SAR systems. The main difference in automotive applications is, that vehicles does not drive with constant speed in straight direction only as planes do. Therefore in this paper a novel algorithm is developed what enables to estimate vehicles ego motion very precisely and at exactly those time steps when it is needed. This algorithm enables both, generating SAR maps as well as autarkic ego motion estimation. Tests in real traffic scenarios show promising results.
KW - Backprojection
KW - EIV problems
KW - Ego motion estimation
KW - SAR
KW - Synthetic aperture radar
UR - http://www.scopus.com/inward/record.url?scp=85097305477&partnerID=8YFLogxK
U2 - 10.23919/IRS48640.2020.9253947
DO - 10.23919/IRS48640.2020.9253947
M3 - Conference contribution
AN - SCOPUS:85097305477
T3 - Proceedings International Radar Symposium
SP - 385
EP - 390
BT - 2020 21st International Radar Symposium, IRS 2020
PB - IEEE Computer Society
T2 - 21st International Radar Symposium, IRS 2020
Y2 - 5 October 2020 through 7 October 2020
ER -