Accelerating short range MIMO imaging with optimized Fourier processing

Journal Article (2020)
Author(s)

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)

A. G. Yarovyi (TU Delft - Microwave Sensing, Signals & Systems)

Research Group
Microwave Sensing, Signals & Systems
Copyright
© 2020 Thomas Fromentèze, Okan Yurduseven, Fabien Berland, Cyril Decroze, David R. Smith, Alexander Yarovoy
DOI related publication
https://doi.org/10.1117/12.2558152
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Thomas Fromentèze, Okan Yurduseven, Fabien Berland, Cyril Decroze, David R. Smith, Alexander Yarovoy
Research Group
Microwave Sensing, Signals & Systems
Volume number
11411
Pages (from-to)
1-6
Reuse Rights

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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.

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