
Proceedings Paper
APES-based procedure for super-resolution SAR imagery with GPU parallel computingFormat | Member Price | Non-Member Price |
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Paper Abstract
The amplitude and phase estimation (APES) algorithm is widely used in modern spectral analysis. Compared with conventional Fourier transform (FFT), APES results in lower sidelobes and narrower spectral peaks. However, in synthetic aperture radar (SAR) imaging with large scene, without parallel computation, it is difficult to apply APES directly to super-resolution radar image processing due to its great amount of calculation. In this paper, a procedure is proposed to achieve target extraction and parallel computing of APES for super-resolution SAR imaging. Numerical experimental are carried out on Tesla K40C with 745 MHz GPU clock rate and 2880 CUDA cores. Results of SAR image with GPU parallel computing show that the parallel APES is remarkably more efficient than that of CPU-based with the same super-resolution.
Paper Details
Date Published: 20 October 2015
PDF: 9 pages
Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 96460C (20 October 2015); doi: 10.1117/12.2194408
Published in SPIE Proceedings Vol. 9646:
High-Performance Computing in Remote Sensing V
Bormin Huang D.D.S.; Sebastián López; Zhensen Wu; Jose M. Nascimento; Boris A. Alpatov; Jordi Portell de Mora, Editor(s)
PDF: 9 pages
Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 96460C (20 October 2015); doi: 10.1117/12.2194408
Show Author Affiliations
Guangyao Xu, BeiHang Univ. (China)
Published in SPIE Proceedings Vol. 9646:
High-Performance Computing in Remote Sensing V
Bormin Huang D.D.S.; Sebastián López; Zhensen Wu; Jose M. Nascimento; Boris A. Alpatov; Jordi Portell de Mora, Editor(s)
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