Optimized Minimum-Search for SAR Backprojection Autofocus on GPUs Using CUDA

verfasst von

Niklas Rother, Christian Fahnemann, Jan Wittler, Holger Christoph Blume

Abstract

Autofocus techniques for synthetic aperture radar (SAR) can improve the image quality substantially. Their high computational complexity imposes a challenge when employing them in runtime-critical implementations. This paper presents an autofocus implementation for stripmap SAR specially optimized for parallel architectures like GPUs. Thorough evaluation using real SAR data shows that the tunable parameters of the algorithm allow to counterbalance runtime and achieved image quality.

Organisationseinheit(en)

Fachgebiet Architekturen und Systeme

Typ

Aufsatz in Konferenzband

Publikationsdatum

2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Elektrotechnik und Elektronik

Elektronische Version(en)

https://doi.org/10.15488/13271 (Zugang: Offen)
https://doi.org/10.1109/RadarConf2043947.2020.9266636 (Zugang: Geschlossen)