Accelerating short range MIMO imaging with optimized Fourier processing

Journal article (2020)

Authors

Thomas Fromenteze University of Limoges
Okan Yurduseven Queen's University Belfast
Fabien Berland University of Limoges
Cyril Decroze University of Limoges
David R. Smith Duke University
Alexander G. Yarovyi Microwave Sensing, Signals & Systems - EEMCS
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
Copyright: © 2020 Thomas Fromentèze, Okan Yurduseven, Fabien Berland, Cyril Decroze, David R. Smith, Alexander Yarovoy
DOI: https://doi.org/10.1117/12.2558152
More Info
expand_more

Published Date

2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

Abstract

In this paper, we describe the recent development of new algorithms applied to short-range radar imaging. Facing the limitations of classical backpropagation algorithms, the use of techniques based on Fast Fourier Transforms has led to substantial image computation accelerations, especially for Multiple-Input Multiple-Output systems. The necessary spatial interpolation and zero-padding steps are still particularly limiting in this context, so it is proposed to replace it by a more efficient matrix technique, showing improvements in memory consumption, image computation speed and reconstruction quality.

Files

114110D.pdf
(pdf | 4.05 Mb)
- Embargo expired in 23-10-2020
Unknown license