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An improved RBR image reconstruction architecture based on super-systolic techniques

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Abstract

In this paper, we address and discuss the time performance improvement achieved with a novel image reconstruction hardware architecture for high-resolution array Radar/SAR imaging. The presented approach is oriented to solve the ill-conditioned inverse spatial spectrum pattern estimation problem via the efficient implementation of super-systolic arrays (SSAs) accelerator units. The co-design-oriented system is addressed to as an aggregated Robust Bayesian-Regularization and SSAs techniques for radar and SAR image reconstruction. We exemplify how this aggregated method leads to a novel real time image reconstruction system as required for newer remote sensing applications. The reported implementation results on a Virtex5 XC5VFX130T Field Programmable Gate Array reveals the significant high-performance improvement over previous works.

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Acknowledgments

This study was supported by Consejo Nacional de Ciencia y Tecnologia (CONACYT), Mexico, under grant CB-2010- 01-158136.

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Authors and Affiliations

  1. Vision, Optimization and Reconfigurable Computing Laboratory, School of Engineering, Universidad Autónoma de Yucatán, Av. Industrias no Contaminantes por Periferico Norte Apdo. Postal 150, Cordemex, Merida, Yucatan, Mexico

    Alejandro Castillo Atoche, Renan Quijano Cetina & Orlando Palma Marrufo

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  1. Alejandro Castillo Atoche
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  2. Renan Quijano Cetina
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  3. Orlando Palma Marrufo
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Correspondence to Orlando Palma Marrufo.

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Castillo Atoche, A., Quijano Cetina, R. & Palma Marrufo, O. An improved RBR image reconstruction architecture based on super-systolic techniques. J Ambient Intell Human Comput 5, 655–666 (2014). https://doi.org/10.1007/s12652-013-0202-y

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