Publication Type:

Conference Paper

Source:

Communications and Signal Processing (ICCSP), 2014 International Conference on, IEEE, Melmaruvathur (2014)

ISBN:

9781479933570

URL:

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6949881

Keywords:

array signal processing, beam steering, communication satellites DBF technique, CPU, Denoising, digital beamforming, geophysical techniques, GPU, graphical processing unit, Graphics processing unit, graphics processing units, high performance computing, HPC, noise, Parallel processing, Radar imaging, SAR data processing, SAR image data, SAR image processing, SAR systems analog beamsteering techniques, Satellites, ScanSAR, smoothing, space-borne Earth observations, space-borne radar satellites, spaceborne radar, Spatial resolution, Spotlight, Standards, Stripmap, Synthetic aperture radar

Abstract:

Synthetic aperture Radar (SAR) has been extensively used for space-borne Earth observations in recent times. In conventional SAR systems analog beamsteering techniques are capable of implementing multiple operational modes, such as the Stripmap, ScanSAR, and Spotlight, to fulfill the different requirements in terms of spatial resolution and coverage. Future RADAR satellites need to resolve the complex issues such as wide area coverage and resolution. Digital beamforming (DBF) is a promising technique to overcome the problems mentioned above. In communication satellites DBF technique is already implemented. This paper discuses the relevance of DBF in space-borne RADAR satellites for enhancements to quality imaging. To implement DBF in SAR, processing of SAR data is an important step. This work focused on processing of Level 1.1 and 1.5 SAR image data. The SAR raw data is computationally intensive to process. To resolve the computation problem, high performance computing (HPC) is necessary. The relevance of HPC for SAR data processing using an off-the-shelf graphical processing unit (GPU) over CPU is discussed in this paper. Quantitative estimates on SAR image processing performance comparisons using both CPU and GPU are also provided as validation for the results.

Cite this Research Publication

S. S. Maddikonda and Dr. Shanmugha Sundaram G. A., “SAR image processing using GPU”, in Communications and Signal Processing (ICCSP), 2014 International Conference on, Melmaruvathur, 2014.

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